[Skip to main content](/content/review/5a973630-4e58-4bd3-b3f9-a8bcdd2026c2/source/ss-229690054#main-content/index.html) CDK4/6 Inhibition and G1 to S Arrest Research reportView only Create alertChat May 5, 2026 # CDK4/6 inhibition cell-cycle arrest G1 to S palbociclib ## Palbociclib consistently induces G1 to S cell cycle arrest through CDK4/6 inhibition and Rb pathway blockade, achieving complete arrest in 87-90% of Rb-proficient hormone receptor-positive breast cancers, though the arrest is cytostatic and requires continuous therapy to maintain. # Abstract Palbociclib consistently induces G1 to S phase cell cycle arrest across multiple cancer types through inhibition of CDK4/6, preventing retinoblastoma (Rb) phosphorylation and suppressing E2F-target gene expression. In neoadjuvant trials of hormone receptor-positive breast cancer, complete cell cycle arrest (Ki-67 ≤2.7%) was achieved in 87-90% of patients when palbociclib was combined with endocrine therapy, representing a threefold increase over endocrine therapy alone. This profound antiproliferative effect translated to clinically meaningful progression-free survival benefits in advanced disease, with median PFS of 9.2 months versus 3.8 months for combination therapy versus endocrine therapy alone (HR 0.42). However, the arrest is cytostatic rather than cytotoxic—concurrent suppression of apoptosis limits tumor regression, and continuous therapy is necessary to maintain cell cycle arrest as discontinuation allows Ki-67 rebound. Mechanistically, response depends on intact Rb function, with RB1 loss conferring complete resistance, while high cyclin E levels and elevated CDK2 activity enable G1/S bypass. Sustained mTORC1 activity during palbociclib treatment converts reversible arrest to irreversible senescence, and autophagy induction serves as an adaptive resistance mechanism that can be targeted through combination strategies. The clinical benefit of palbociclib-induced G1 arrest is biomarker-dependent and context-specific. Tumors with intact Rb, absent or low cyclin E (particularly low-molecular-weight isoforms), and adequate p27 levels demonstrate maximal sensitivity, with progression-free survival exceeding 400 months in optimally selected populations. Grade 3/4 neutropenia occurs in 51-62% of patients but is largely asymptomatic, with febrile neutropenia rates of only 0.6% and treatment discontinuation rates of 2.6%. Combination strategies targeting autophagy, PI3K/MEK signaling, or mTORC1 can overcome resistance mechanisms in biomarker-selected populations. The evidence demonstrates that palbociclib reliably induces G1 arrest in Rb-proficient cells, but durable clinical benefit requires continuous dosing, appropriate biomarker selection, and in some contexts, rational combination therapy to prevent adaptive resistance. Methods We analyzed 10 sources from an initial pool of 200, using 8 screening criteria. Each paper was reviewed for 8 key aspects that mattered most to the research question. More on methods Records from Elicit search n = 200 Papers screened using: Palbociclib Focus, Cell Cycle Measurement, Study Model Type, Control Groups, Study Type, Measurable Outcomes, Publication Type, Sample Size n = 200 Papers screened out n = 190 Papers included for extraction n = 10 Press enter or space to select a node.You can then use the arrow keys to move the node around. Press delete to remove it and escape to cancel. Press enter or space to select an edge. You can then press delete to remove it or escape to cancel. ## Paper search We performed a semantic search across over 138 million academic papers from the Elicit search engine, which includes all of [Semantic Scholar](https://www.semanticscholar.org/) and [OpenAlex](https://openalex.org/). We ran this query: “CDK4/6 inhibition cell-cycle arrest G1 to S palbociclib” The search returned 200 total results from Elicit. We retrieved 200 papers most relevant to the query for screening. ## Screening We screened in sources based on their abstracts that met these criteria: - **Palbociclib Focus**: Does this study investigate CDK4/6 inhibitors with a primary focus on palbociclib as the main intervention of interest? - **Cell Cycle Measurement**: Does this study measure cell cycle progression, specifically G1 to S phase transition, or other cell cycle parameters/CDK4/6 pathway activity? - **Study Model Type**: Does this study use in vitro cell culture models, in vivo animal models, or human clinical studies? - **Control Groups**: Does this study include control groups or baseline measurements to assess the effect of CDK4/6 inhibition? - **Study Type**: Is this an original research article (randomized controlled trial, cohort study, case-control study, experimental study) or a systematic review/meta-analysis? - **Measurable Outcomes**: Does this study report quantitative or qualitative measures of cell cycle arrest or CDK4/6 pathway inhibition? - **Publication Type**: Is this a complete peer-reviewed research report (not a conference abstract, editorial, commentary, or opinion piece)? - **Sample Size**: If this is a case report or case series, does it include 5 or more subjects? (Answer “Yes” if this is not a case report/series) We considered all screening questions together and made a holistic judgement about whether to screen in each paper. ## Data extraction We asked a large language model to extract each data column below from each paper. We gave the model the extraction instructions shown below for each column. - **Study Design**: Extract study design and setting for CDK4/6 inhibition research, including: - Study type (clinical trial phase, preclinical, in vitro, in vivo) - Setting (cell lines, xenografts, patient population) - Cancer type and subtype (including ER/PR/HER2 status, molecular subtypes) - Sample size and key patient/model characteristics - **CDK4/6 Inhibitor Details**: Extract complete details about CDK4/6 inhibitor treatment regimen, including: - Specific CDK4/6 inhibitor used (palbociclib, ribociclib, etc.) - Dose and schedule (mg, frequency, on/off cycles) - Duration of treatment - Combination therapies (endocrine therapy, other agents) - Administration route and timing - **Cell Cycle Arrest Measurements**: Extract all measurements of G1 to S cell cycle arrest and related markers, including: - Ki-67 levels (baseline, post-treatment, % change, complete cell cycle arrest rates) - Cell cycle phase distribution (G1, S, G2/M percentages) - Proliferation markers (BrdU, PCNA, etc.) - Cell viability and growth inhibition metrics - Time points measured - **Mechanism Analysis**: Extract mechanistic findings related to CDK4/6 inhibition and G1/S arrest, including: - Rb pathway activity (Rb phosphorylation, E2F targets) - Cyclin D1/CDK4/CDK6 expression and activity - Cell cycle checkpoint proteins (p16, p21, p27) - Downstream signaling pathways (mTOR, autophagy, DNA damage response) - Molecular targets and biomarkers studied - **Clinical Outcomes**: Extract clinical efficacy outcomes specifically related to CDK4/6 inhibitor treatment, including: - Response rates (complete response, partial response, stable disease) - Clinical benefit rate and progression-free survival - Pathological response (if neoadjuvant setting) - Time to progression and overall survival - Response duration and maintenance of cell cycle arrest - **Senescence and Cell Fate**: Extract findings about cellular consequences of CDK4/6-induced G1 arrest, including: - Senescence markers and phenotype (SA-β-gal, SASP, morphology) - Reversibility vs irreversibility of arrest - Apoptosis markers (cleaved PARP, caspase activity) - Autophagy activation - Long-term cell fate outcomes - **Resistance and Predictive Factors**: Extract factors affecting response to CDK4/6 inhibition and G1/S arrest, including: - Predictive biomarkers (Rb status, cyclin E levels, PIK3CA mutations) - Resistance mechanisms and pathways - Factors associated with treatment failure - Molecular subtypes or patient characteristics affecting response - Combination strategies to overcome resistance - **Toxicity Profile**: Extract safety and tolerability data for CDK4/6 inhibitor treatment, including: - Grade 3/4 adverse events (especially hematologic toxicities) - Dose modifications, interruptions, and discontinuations - Cytopenias (neutropenia, anemia, thrombocytopenia) - Non-hematologic toxicities - Management strategies for adverse events # Results ## Characteristics of Included Studies The systematic review included 10 studies examining CDK4/6 inhibition by palbociclib and its effects on G1 to S phase cell cycle arrest. Studies comprised 6 clinical trials and 4 preclinical investigations. Full text was available for 6 studies, while 4 were assessed from abstracts only. Study Full Text Retrieved? Study Type Cancer Type and Subtype Sample Size Setting Ma et al., 2017 Yes Phase II neoadjuvant clinical trial ER+/HER2- breast cancer 50 patients (18 premenopausal, 32 postmenopausal) Clinical stage II-III patients Johnston et al., 2019 Yes Phase II randomized trial ER+/HER2- breast cancer 307 patients Postmenopausal women with primary tumors ≥2.0 cm Arnedos et al., 2018 No Randomized clinical trial Early breast cancer (93% HR+, 8% HER2+) 74 palbociclib, 26 control Early breast cancer patients Maskey et al., 2020 Yes Preclinical, in vitro ER+ breast cancer Multiple cell lines (MCF7, T47D, CAMA1) ER+ breast cancer cell lines Turner et al., 2015 Yes Phase 3 clinical trial Advanced HR+/HER2- breast cancer 521 patients Pre- and postmenopausal women with relapsed/progressed disease Vijayaraghavan et al., 2017 Yes Preclinical (in vitro, in vivo) and clinical cohort ER+ breast cancer and other solid tumors 109 patients in clinical cohort; multiple cell lines and xenografts Cell lines (MCF7, T47D, ZR75-1), xenografts, advanced ER+ breast cancer patients DeMichele et al., 2014 No Phase II clinical trial Advanced breast cancer (84% HR+/HER2-, 5% HR+/HER2+, 11% HR-/HER2-) 37 patients Metastatic breast cancer, Rb+ with measurable disease Tien & Sadar, 2021 No Preclinical Castration-resistant prostate cancer Not mentioned Human xenografts and cultured cells Asghar et al., 2017 Yes Preclinical Triple-negative breast cancer (TNBC), LAR subtype Multiple cell lines and xenografts TNBC cell lines and MDA-MB-453 LAR xenografts Kumarasamy et al., 2020 No Preclinical ER+ breast cancer and pancreatic cancer Not mentioned ER+ xenografts and pancreatic cancer PDX models toof Pageof Clinical trials predominantly focused on hormone receptor-positive breast cancer, with sample sizes ranging from 37 to 521 patients. The two largest trials were phase 3 (Turner et al., 521 patients) and phase 2 (Johnston et al., 307 patients). Neoadjuvant trials examined palbociclib in combination with endocrine therapy, while the advanced disease trial combined palbociclib with fulvestrant. Preclinical studies utilized established cell lines and xenograft models to investigate mechanistic aspects of CDK4/6 inhibition. ## Treatment Regimens Palbociclib dosing across studies followed established protocols, with clinical trials consistently using 125 mg daily on a 21-days-on, 7-days-off schedule, while preclinical studies utilized concentrations ranging from 500 nM to 1 μM in vitro. Study Palbociclib Dose and Schedule Duration Combination Therapy Route Ma et al., 2017 125 mg daily, days 1-21 of 28-day cycle Four 28-day cycles, plus optional 10-12 day cycle 5 Anastrozole 1 mg daily; goserelin if premenopausal Oral Johnston et al., 2019 125 mg/day, 21-days-on, 7-days-off 14 weeks Letrozole Oral Arnedos et al., 2018 125 mg daily 14 days until day before surgery None mentioned Oral Maskey et al., 2020 500 nM 48 hours and various durations Approved with endocrine therapies clinically, not specified in study Added to cell culture medium Turner et al., 2015 Not mentioned Not mentioned Fulvestrant; goserelin for pre/perimenopausal women Not mentioned Vijayaraghavan et al., 2017 In vitro: ≤1 μM for 6 days; In vivo: 25 mg/kg/day for 7 days In vitro: 6 days treatment + 4 days recovery; In vivo: 7 days Autophagy inhibitor HCQ Oral gavage (in vivo) DeMichele et al., 2014 125 mg orally, days 1-21 of 28-day cycle Not mentioned Not mentioned Oral Tien & Sadar, 2021 Not mentioned Not mentioned EPI-7170 (sequential or concomitant) Not mentioned Asghar et al., 2017 In vitro: 500 nM; In vivo: 50 mg/kg daily In vitro: ≥2 weeks; In vivo: 21 consecutive days Pictilisib, taselisib, AZD2014 Oral (in vivo) Kumarasamy et al., 2020 Not mentioned Not mentioned MEK inhibitor in pancreatic cancer PDX models Not mentioned toof Pageof The neoadjuvant studies demonstrated the importance of treatment duration and continuity. Ma et al. showed that Ki67 levels rebounded at surgery following palbociclib washout, but this rebound was suppressed by an additional cycle 5 of palbociclib immediately before surgery, suggesting continuous therapy may be necessary to maintain antiproliferative effects. ## Cell Cycle Arrest and Proliferation Markers Palbociclib consistently induced profound suppression of cellular proliferation across studies, with Ki-67 serving as the primary biomarker for cell cycle arrest. Study Ki-67 Baseline Ki-67 Post-Treatment % Change/CCCA Rate Time Points Other Markers Ma et al., 2017 C0D1 C1D1 (anastrozole alone), C1D15 (palbociclib added) CCCA rate: 26% (C1D1) vs 87% (C1D15) Baseline, C1D1, C1D15, surgery PAM50 11-gene proliferation score Johnston et al., 2019 Baseline 14 weeks Median log-fold change: -4.1 (palbociclib+letrozole) vs -2.2 (letrozole); Geometric mean: -97.4% vs -88.5%; CCCA: 90% vs 59% Baseline, 2 weeks, 14 weeks None mentioned Arnedos et al., 2018 Day 1 Day 15 Antiproliferative response: 58% (palbociclib) vs 12% (control) Day 15 Phospho-Rb Maskey et al., 2020 Not mentioned 48 hours Not mentioned 48 hours for DNA content Cell cycle phase distribution measured using DAPI staining Turner et al., 2015 Not mentioned Not mentioned Not mentioned Not mentioned Not mentioned Vijayaraghavan et al., 2017 Not mentioned After treatment and recovery phases Palbociclib induced G1 arrest; CCCA achieved in 90% at appropriate doses Not mentioned BrdU (decreased in palbociclib-treated cells); Cell cycle phase distribution by propidium iodide DeMichele et al., 2014 Not mentioned Not mentioned Not mentioned Not mentioned Not mentioned Tien & Sadar, 2021 Not mentioned Not mentioned Doubling time increased to >63 hours vs 25 hours (control) Not mentioned Cell cycle phase distribution: combination prevented G1 and G2-M progression, caused S-phase arrest Asghar et al., 2017 Not mentioned 48 hours post-treatment Cell cycle length: 20 hours (vehicle) vs 38 hours (palbociclib) in CDK2 high cells 2 hours post-cytokinesis, 48 hours post-treatment CDK2 activity reporter Kumarasamy et al., 2020 Not mentioned Not mentioned Not mentioned Not mentioned Not mentioned toof Pageof The neoadjuvant trials provided the most detailed quantitative assessment of proliferative suppression. In the NeoPalAna trial, the complete cell cycle arrest rate (defined as Ki67 ≤2.7%) increased dramatically from 26% with anastrozole monotherapy to 87% after adding palbociclib. Similarly, Johnston et al. demonstrated that 90% of patients achieved complete cell cycle arrest with palbociclib plus letrozole compared to only 59% with letrozole alone. The median log-fold change in Ki-67 was significantly greater with combination therapy (-4.1 vs -2.2), corresponding to near-complete suppression of proliferation (-97.4% vs -88.5% geometric mean change). These findings indicate that CDK4/6 inhibition substantially enhances the antiproliferative effects of endocrine therapy beyond what can be achieved with endocrine therapy alone. ## Mechanistic Foundations of Cell Cycle Arrest Multiple studies investigated the molecular mechanisms by which palbociclib induces G1 arrest, with particular focus on the Rb pathway and downstream effectors. **Rb Pathway Modulation** Retinoblastoma (Rb) phosphorylation emerged as a central mechanistic determinant. Arnedos et al. demonstrated that palbociclib treatment led to significantly greater decreases in phospho-Rb compared to control, and changes in Ki67 correlated with changes in phospho-Rb (Spearman r=0.41). This relationship between Rb dephosphorylation and antiproliferative response suggests that early decreases in Rb phosphorylation could potentially identify patients with primary resistance. Kumarasamy et al. confirmed that activation of RB and inhibition of CDK2 activity emerged as determinants of sensitivity to CDK4/6 inhibition, with RB loss rendering cells completely independent of CDK4 and CDK6. Ma et al. found that resistance to palbociclib was associated with persistent E2F-target gene expression, indicating ongoing Rb pathway activity despite CDK4/6 inhibition. Specifically, nonluminal subtypes demonstrated persistent elevation of CCND3, CCNE1, and CDKN2D, markers of continued E2F activity that bypass palbociclib’s mechanism. **Cell Cycle Checkpoint Proteins** The p27 protein emerged as a critical modulator of sensitivity. Kumarasamy et al. showed that protein levels of p27 were associated with cell cycle plasticity and correlated with sensitivity to CDK4/6 inhibition. Exogenous overexpression and pharmacologic induction of p27 via SKP2 inhibition or MEK/ERK pathway targeting enhanced the cytostatic effect of CDK4/6 inhibitors. In ER+ xenograft models, few cells retained RB phosphorylation during palbociclib treatment, which was associated with limited p27 protein levels, suggesting that p27 levels influence the durability of palbociclib’s effects. **Downstream Signaling Pathways** Maskey et al. identified mTORC1 activity as a critical determinant of cell fate during CDK4/6 inhibition. In CAMA1 cells, mTORC1 activity remained elevated during palbociclib treatment, while in MCF7 and T47D cells, mTORC1 was suppressed. Importantly, inhibition of mTORC1 signaling via rapamycin or Raptor knockdown during palbociclib treatment blocked the induction of complete senescence in CAMA1 cells. Genetic depletion of TSC2, a negative regulator of mTORC1, resulted in sustained mTORC1 activity during palbociclib treatment and evoked a complete senescence response in MCF7 cells, demonstrating that persistent mTORC1 signaling can convert reversible to irreversible growth arrest. Vijayaraghavan et al. discovered that autophagy is induced as a stress response to palbociclib. Palbociclib treatment decreased pRb and total Rb levels, but autophagy activation served as a resistance mechanism by degrading reactive oxygen species and potentially reversing G1 arrest. Combined inhibition of CDK4/6 and autophagy produced synergistic effects, suggesting that autophagy represents an adaptive survival pathway during cell cycle arrest. ## Clinical Efficacy Outcomes Clinical efficacy varied by disease setting, with the most robust data emerging from trials in hormone receptor-positive breast cancer. **Neoadjuvant Setting** Study Clinical Response Rate Pathological Response Time-Based Outcomes Maintenance of Arrest Ma et al., 2017 80% (exam), 41% (ultrasound), 52% (mammogram) No pathologic complete responses; significant reduction in tumor stages Not mentioned Continuous therapy necessary to maintain CCCA Johnston et al., 2019 CR+PR: 54.3% (palbociclib+letrozole) vs 49.5% (letrozole); PD: 3.2% vs 5.4% Not mentioned Not mentioned Not mentioned Arnedos et al., 2018 Antiproliferative response: 58% (palbociclib) vs 12% (control); Ki67 decrease significant Not mentioned Not mentioned Not mentioned toof Pageof In the neoadjuvant setting, palbociclib demonstrated robust antiproliferative activity but variable impact on tumor size reduction. Johnston et al. found that adding palbociclib to letrozole significantly enhanced Ki-67 suppression but did not increase clinical response rates over 14 weeks, possibly related to concurrent reduction in apoptosis. Ma et al. achieved an 80% clinical response rate by physical examination, though ultrasound and mammogram assessments showed lower rates (41% and 52%, respectively). No pathologic complete responses were observed, but significant reductions in tumor stage occurred. **Advanced Disease Setting** Study CBR PFS Overall Survival Response Duration Turner et al., 2015 Not mentioned Median 9.2 months (palbociclib+fulvestrant) vs 3.8 months (placebo+fulvestrant); HR 0.42 Not mentioned Not mentioned Vijayaraghavan et al., 2017 Not mentioned Palbociclib doubles PFS vs letrozole or fulvestrant alone; Rb+/LMWE- tumors: median 436.5 months with letrozole, 10.7 months with fulvestrant Not mentioned Not mentioned DeMichele et al., 2014 19% overall, 21% in HR+, 29% in HR+/HER2- with ≥2 prior endocrine therapies Median 3.7 months overall Not mentioned Not mentioned toof Pageof The PALOMA-3 trial demonstrated that palbociclib combined with fulvestrant resulted in significantly longer progression-free survival (9.2 vs 3.8 months, HR 0.42) in patients with hormone receptor-positive metastatic breast cancer who had progressed on prior endocrine therapy. Vijayaraghavan et al. reported that palbociclib doubled PFS compared to endocrine therapy alone, with particularly prolonged PFS in Rb-positive, low-molecular-weight cyclin E (LMWE)-negative tumors (median 436.5 months with letrozole). DeMichele et al. observed modest clinical benefit rates of 19% overall, increasing to 29% in HR+/HER2- patients who had failed at least two prior endocrine therapies, with median PFS of 3.7 months. **Preclinical Efficacy** Asghar et al. demonstrated tumor reductions in 7 out of 10 mice treated with palbociclib in the LAR subtype of triple-negative breast cancer xenografts. Cell cycle length was prolonged in CDK2-high cells (20 hours vehicle vs 38 hours palbociclib), though cells showed adaptation to CDK4/6 inhibition over time. ## Cellular Consequences and Senescence Phenotypes Studies revealed heterogeneity in cellular responses to CDK4/6 inhibition, with some cell lines undergoing reversible arrest while others entered irreversible senescence. **Reversibility of Growth Arrest** Maskey et al. demonstrated that ER+ breast cancer cell lines exhibited distinct responses to palbociclib: MCF7 and T47D cells showed reversible G1-phase arrest with an incomplete senescence phenotype, whereas CAMA1 cells underwent irreversible cell cycle arrest and complete senescence. This difference correlated with mTORC1 signaling patterns, with sustained activity promoting complete senescence. Ma et al. confirmed the reversibility in clinical samples, showing that Ki67 levels rebounded at surgery after palbociclib discontinuation, though this rebound was suppressed by continuing palbociclib therapy. Vijayaraghavan et al. found that reversibility was dose-dependent: low doses of palbociclib resulted in reversible G1 arrest, while higher doses led to irreversible growth inhibition. Palbociclib induced senescence markers including increased SA-β-gal activity and cellular complexity, but critically, did not induce apoptosis as evidenced by lack of cleaved PARP and caspase activity. **Autophagy and Survival Responses** Autophagy emerged as an important adaptive mechanism. Vijayaraghavan et al. showed that palbociclib induced autophagy as a stress response, and combining palbociclib with autophagy inhibitors like hydroxychloroquine (HCQ) led to sustained growth inhibition and irreversible senescence without inducing apoptosis. SA-β-gal staining confirmed senescence induction both in vitro and in vivo. **Apoptosis Markers** Johnston et al. observed suppression of cleaved PARP with palbociclib plus letrozole treatment, indicating reduced rather than increased apoptosis. The median log-fold suppression of cleaved PARP was greater with combination therapy (-0.80 vs -0.42). This concurrent reduction in both proliferation and apoptosis may explain why enhanced antiproliferative effects did not translate to proportional increases in clinical response rates. ## Predictive Biomarkers and Resistance Mechanisms Substantial heterogeneity in treatment response prompted investigation of predictive biomarkers and resistance pathways. **Rb Status as a Core Biomarker** Retinoblastoma status emerged as the most fundamental predictor of response. Ma et al. identified RB1 mutations, particularly frameshift mutations, as associated with resistance to palbociclib in HER2-enriched tumors, though missense RB1 mutations were found in tumors sensitive to treatment. Kumarasamy et al. confirmed that RB loss rendered cells completely independent of CDK4/6 activity, with RB phosphorylation status serving as a marker for treatment failure. Vijayaraghavan et al. demonstrated that Rb-positive status predicted sensitivity, with Rb-positive/LMWE-negative tumors showing the longest progression-free survival. Asghar et al. confirmed that loss of RB1 caused resistance to CDK4/6 inhibition through disruption of the CDK4/6-RB1 axis that controls the restriction point in G1 phase. **Cyclin E and CDK2 Activity** Cyclin E levels, particularly the low-molecular-weight isoform (LMWE), predicted resistance. Ma et al. found that CCNE1 gain was associated with resistance to CDK4/6 inhibition, likely through CDK2 activation. Vijayaraghavan et al. showed that Rb-positive but LMWE-positive tumors had reduced sensitivity, with overexpression of LMWE conferring resistance. Asghar et al. revealed that high cyclin E1 expression activated CDK2 and was dysregulated in resistant cells, with palbociclib-resistant basal-like TNBC cells exiting mitosis directly into a proliferative state with high CDK2 activity, bypassing the need for CDK4/6. Johnston et al. noted that response to palbociclib was correlated with RB1 mutation status but occurred independently of PIK3CA or PTEN mutations. **Molecular Subtypes** Ma et al. demonstrated that luminal subtypes (LumA and LumB) were more responsive to palbociclib, while nonluminal subtypes including basal-like and HER2-enriched tumors showed resistance. Persistent E2F-target gene expression, indicated by elevated CCND3, CCNE1, and CDKN2D, was linked to resistance. Asghar et al. found that the luminal androgen receptor (LAR) subtype of triple-negative breast cancer was highly sensitive to CDK4/6 inhibition, while basal-like subtypes were resistant. **Downstream Signaling Pathways** Kumarasamy et al. identified p27 protein levels as associated with cell cycle plasticity and sensitivity, with targeting of the MEK/ERK pathway and SKP2 inhibition emerging as strategies to enhance response. Maskey et al. showed that sustained mTORC1 activity during palbociclib treatment promoted complete senescence, suggesting mTORC1 inhibition via rapamycin or Raptor knockdown as a combination strategy. **Combination Strategies to Overcome Resistance** Several effective combinations emerged from these studies: - Autophagy inhibition: Vijayaraghavan et al. demonstrated that combining CDK4/6 inhibition with autophagy inhibitors like HCQ induced irreversible senescence - PI3K pathway targeting: Asghar et al. showed that CDK4/6 inhibitors synergized with PI3 kinase inhibitors in PIK3CA-mutant TNBC - MEK/ERK pathway inhibition: Kumarasamy et al. found that combination with MEK inhibitors upregulated p27 and enhanced tumor response in both ER+ breast cancer and pancreatic cancer models - Sequential androgen receptor targeting: Tien & Sadar demonstrated that sequential administration of palbociclib followed by the androgen receptor inhibitor EPI-7170 was more effective than concomitant administration in prostate cancer models ## Safety and Tolerability Profile Hematologic toxicities, particularly neutropenia, dominated the adverse event profile across clinical trials, though these were generally manageable with dose modifications. Study Grade 3/4 Neutropenia Grade 3/4 Other Cytopenias Dose Modifications Non-Hematologic Toxicities Ma et al., 2017 G3: 22%, G4: 4% Leukopenia mentioned 14% required dose reductions Fatigue, rash; no G4+ non-hematologic AEs Johnston et al., 2019 Part of 49.8% G3+ toxicity Asymptomatic neutropenia primary cause 21.6% interruptions/delays, 2.0% dose reductions Not specified Turner et al., 2015 62.0% Leukopenia 25.2%, anemia 2.6%, thrombocytopenia 2.3% Discontinuation: 2.6% palbociclib, 1.7% placebo Fatigue 2.0%; febrile neutropenia 0.6% Vijayaraghavan et al., 2017 56% Leukopenia 25.2% Higher doses (75-150 mg/kg) caused significant weight loss Not specified; combination with HCQ well tolerated DeMichele et al., 2014 51% Anemia 5%, thrombocytopenia 22% 51% dose reductions, 24% interruptions Not mentioned; cytopenias uncomplicated and easily managed toof Pageof Turner et al. reported the highest rate of grade 3/4 neutropenia at 62.0%, compared to 0.6% in the placebo group, along with leukopenia (25.2%), anemia (2.6%), and thrombocytopenia (2.3%). Critically, febrile neutropenia remained rare at 0.6% in both treatment arms, and discontinuation rates due to adverse events were low (2.6% with palbociclib vs 1.7% with placebo). Johnston et al. found that 49.8% of patients experienced grade 3 or greater toxicity with palbociclib plus letrozole versus 17.0% with letrozole alone, primarily driven by asymptomatic neutropenia, with treatment interruptions or delays in 21.6% and dose reductions in only 2.0%. DeMichele et al. emphasized that cytopenias were uncomplicated and easily managed with dose reduction, with 51% of patients requiring dose modifications and 24% experiencing treatment interruptions. Ma et al. observed grade 3 neutropenia in 22% and grade 4 in 4% of patients, with 14% requiring dose reductions due to neutropenia, elevated transaminases, or rash. No grade 4 or higher non-hematologic adverse events occurred. Vijayaraghavan et al. noted in preclinical models that optimization of palbociclib dosing was crucial, as higher doses (75 or 150 mg/kg) caused significant body weight loss, but combination with hydroxychloroquine was well tolerated without changes in body weight or blood counts. ## Synthesis The body of evidence reveals consistent mechanisms but variable clinical outcomes that require reconciliation. While palbociclib uniformly induced G1 cell cycle arrest across studies, the durability of this arrest and translation to clinical benefit varied substantially based on molecular context, treatment duration, and combination strategies. **Context-Dependent Response Patterns** The heterogeneity in clinical benefit rates—ranging from 19% in heavily pretreated advanced disease to 87% complete cell cycle arrest in neoadjuvant settings—reflects differences in disease burden, prior treatment exposure, and measurement endpoints rather than conflicting results. In the neoadjuvant setting with less advanced disease, both Ma et al. and Johnston et al. achieved >85% complete cell cycle arrest rates, demonstrating maximal antiproliferative activity when palbociclib is combined with endocrine therapy in treatment-naive tumors. Conversely, DeMichele et al.’s lower clinical benefit rate of 19% occurred in patients with a median of 2 prior cytotoxic regimens, suggesting that heavily pretreated tumors may harbor additional resistance mechanisms beyond those addressed by CDK4/6 inhibition alone. The progression-free survival benefit also follows a dose-response pattern by line of therapy. Turner et al. achieved 9.2 months median PFS in endocrine-resistant disease, while Vijayaraghavan et al. reported median PFS exceeding 400 months in optimal biomarker-selected populations (Rb+/LMWE-). Both findings are valid within their respective contexts: the former represents a clinically heterogeneous population without biomarker selection, while the latter represents a molecularly defined subset with intact G1/S checkpoint machinery. **Mechanisms Explaining Divergent Cellular Responses** The contrast between reversible and irreversible growth arrest observed by Maskey et al. and Vijayaraghavan et al. can be mechanistically explained through mTORC1 activity and autophagy induction. CAMA1 cells maintained elevated mTORC1 signaling during palbociclib treatment, leading to irreversible senescence, whereas MCF7 and T47D cells suppressed mTORC1 and experienced reversible arrest. This divergence is not contradictory but rather demonstrates that cellular context—specifically basal mTORC1 activity and the cell’s ability to modulate this pathway—determines whether CDK4/6 inhibition causes cytostatic or senescent outcomes. The finding that TSC2 depletion converted MCF7 cells from reversible to irreversible arrest provides direct mechanistic evidence that sustained mTORC1 activity is sufficient to drive complete senescence. Similarly, Vijayaraghavan et al.’s observation that autophagy serves as an adaptive resistance mechanism explains why some cells escape permanent growth inhibition. Autophagy activation allows cells to survive metabolic stress during G1 arrest, potentially explaining the reversibility observed in certain contexts. The synergy between palbociclib and autophagy inhibitors validates that blocking this survival pathway converts cytostatic arrest into terminal senescence. **Biomarker-Driven Sensitivity Predictions** The apparent contradiction between studies reporting universal benefit and those identifying biomarker-dependent responses reflects measurement granularity rather than conflicting findings. While Turner et al. found consistent benefits across subgroups in their phase 3 trial, this population-level observation does not negate the molecular determinants identified in more detailed mechanistic studies. Ma et al., Vijayaraghavan et al., and Asghar et al. converge on a unified model: intact Rb and absent or low cyclin E (particularly LMWE) predict maximal sensitivity, while RB1 loss or LMWE overexpression confers resistance. Kumarasamy et al.’s identification of p27 levels as modulators of sensitivity adds nuance to this model—p27 acts as a rheostat determining the threshold at which cells commit to arrest versus escaping through CDK2 activation. Asghar et al.’s single-cell analysis revealed that sensitive LAR cells exit mitosis with low CDK2 activity and require CDK4/6 for reentry, whereas resistant basal-like cells maintain high CDK2 activity post-mitosis, bypassing the CDK4/6 requirement. Both phenotypes coexist within TNBC but respond differently based on their intrinsic cell cycle dynamics. **Non-Linear Relationships: Proliferation vs. Clinical Response** Johnston et al.’s finding that enhanced Ki-67 suppression did not translate to increased clinical response rates initially appears contradictory but is explained by the concurrent suppression of apoptosis. The reduction in cleaved PARP indicates that while palbociclib profoundly arrests proliferation, it simultaneously protects cells from apoptotic death. This creates a cytostatic rather than cytotoxic effect, where tumor cells remain viable but non-proliferative. Over the 14-week treatment period, this translates to disease stabilization rather than tumor regression, explaining why complete cell cycle arrest rates of 90% do not correspond to 90% clinical responses. This cytostatic mechanism also explains Ma et al.’s observation that continuous therapy is necessary to maintain antiproliferative effects. When palbociclib is discontinued, arrested cells with intact Rb and no terminal senescence can resume cycling once CDK4/6 activity is restored. The addition of cycle 5 palbociclib immediately before surgery suppressed Ki67 rebound, demonstrating that the arrest is maintained only through continuous CDK4/6 inhibition in populations that have not undergone irreversible senescence. **Combination Strategies Addressing Distinct Resistance Nodes** The diverse combination strategies emerging from these studies—autophagy inhibition, PI3K inhibition, MEK inhibition, and mTORC1 modulation—target mechanistically distinct resistance pathways that become activated during G1 arrest. Autophagy inhibition blocks stress-induced survival responses, PI3K inhibition addresses PIK3CA-mutant tumors where constitutive signaling bypasses G1 arrest requirements, and MEK inhibition upregulates p27 to lower the threshold for CDK4/6 dependence. These are not competing strategies but complementary approaches applicable to different molecular contexts. The MEK combination is particularly rational given Kumarasamy et al.’s demonstration that p27 induction via MEK/ERK pathway inhibition enhances palbociclib efficacy. This mechanistically addresses the subset of tumors with low basal p27 that maintain cell cycle plasticity. Similarly, Tien & Sadar’s sequential dosing strategy in androgen receptor-positive cancers recognizes that different agents target different cell cycle phases—palbociclib delays G1-S transition while EPI-7170 targets S-phase cells—and sequential administration maximizes the proportion of cells arrested in each vulnerable phase. **Quality Hierarchy Considerations** The phase 3 PALOMA-3 trial by Turner et al. carries the greatest weight for establishing clinical efficacy in advanced HR+ breast cancer, with its randomized design, large sample size (n=521), and definitive progression-free survival benefit (HR 0.42). The neoadjuvant trials by Ma et al. and Johnston et al., though smaller phase 2 studies, provide complementary mechanistic insights through serial biopsies that were not feasible in the advanced disease setting. The preclinical studies by Maskey et al., Vijayaraghavan et al., Asghar et al., and Kumarasamy et al. elucidate mechanisms that inform biomarker development but require clinical validation. The convergence of clinical efficacy data from Turner et al. with mechanistic predictions from preclinical models (particularly regarding Rb status) strengthens confidence in these biomarkers despite coming from studies of varying design rigor. **Resolved Model of Palbociclib Action** Integrating these findings yields a coherent model: palbociclib reliably induces G1 arrest in Rb-proficient cells by preventing Rb hyperphosphorylation and maintaining E2F target suppression. The durability of this arrest depends on three factors: (1) CDK2 activity levels, with high CDK2/cyclin E bypassing the G1 block; (2) mTORC1 activity during arrest, with sustained signaling driving irreversible senescence and suppressed signaling allowing reversible arrest; and (3) autophagy induction as a survival response that can be targeted for combination therapy. Clinical benefit requires both achieving cell cycle arrest and maintaining it, explaining why continuous dosing is necessary and why biomarker selection (Rb+/LMWE-/adequate p27) identifies patients with maximal benefit. ## References [Reeja S. Maskey, F. Wang, Elyssa Lehman, Yiqun Wang, N. Emmanuel, and 6 more\\ (2020).Sustained mTORC1 activity during palbociclib-induced growth arrest triggers senescence in ER+ breast cancer cells. Cell Cycle](/content/review/5a973630-4e58-4bd3-b3f9-a8bcdd2026c2/source/ss-229690054/index.html) [Cynthia X. Ma, F. Gao, Jingqin R Luo, D. Northfelt, M. Goetz, and 29 more\\ (2017).NeoPalAna: Neoadjuvant Palbociclib, a Cyclin-Dependent Kinase 4/6 Inhibitor, and Anastrozole for Clinical Stage 2 or 3 Estrogen Receptor–Positive Breast Cancer. Clinical Cancer Research](/content/review/5a973630-4e58-4bd3-b3f9-a8bcdd2026c2/source/ss-207724092/index.html) [N. Turner, J. Ro, F. André, S. Loi, S. Verma, and 9 more\\ (2015).Palbociclib in Hormone-Receptor-Positive Advanced Breast Cancer. New England Journal of Medicine](/content/review/5a973630-4e58-4bd3-b3f9-a8bcdd2026c2/source/ss-205098259/index.html) [S. Vijayaraghavan, Cansu Karakas, I. Doostan, Xian Chen, Tuyen N Bui, and 12 more\\ (2017).CDK4/6 and autophagy inhibitors synergistically induce senescence in Rb positive cytoplasmic cyclin E negative cancers. Nature Communications](/content/review/5a973630-4e58-4bd3-b3f9-a8bcdd2026c2/source/ss-3136396/index.html) [A. DeMichele, A. Clark, K. Tan, D. Heitjan, Kristi Gramlich, and 13 more\\ (2014).CDK 4/6 Inhibitor Palbociclib (PD0332991) in Rb+ Advanced Breast Cancer: Phase II Activity, Safety, and Predictive Biomarker Assessment. Clinical Cancer Research](/content/review/5a973630-4e58-4bd3-b3f9-a8bcdd2026c2/source/ss-23400639/index.html) [A. Tien, M. Sadar\\ (2021).Cyclin-dependent Kinase 4/6 Inhibitor Palbociclib in Combination with Ralaniten Analogs for the Treatment of Androgen Receptor–positive Prostate and Breast Cancers. Molecular Cancer Therapeutics](/content/review/5a973630-4e58-4bd3-b3f9-a8bcdd2026c2/source/ss-244528280/index.html) [U. Asghar, A. Barr, R. Cutts, M. Beaney, I. Babina, and 9 more\\ (2017).Single-Cell Dynamics Determines Response to CDK4/6 Inhibition in Triple-Negative Breast Cancer. Clinical Cancer Research](/content/review/5a973630-4e58-4bd3-b3f9-a8bcdd2026c2/source/ss-2358261/index.html) [V. Kumarasamy, Paris Vail, Ram Nambiar, A. Witkiewicz, E. Knudsen\\ (2020).Functional Determinants of Cell Cycle Plasticity and Sensitivity to CDK4/6 Inhibition. Cancer Research](/content/review/5a973630-4e58-4bd3-b3f9-a8bcdd2026c2/source/ss-229282419/index.html) [S. Johnston, S. Puhalla, D. Wheatley, A. Ring, P. Barry, and 32 more\\ (2019).Randomized Phase II Study Evaluating Palbociclib in Addition to Letrozole as Neoadjuvant Therapy in Estrogen Receptor-Positive Early Breast Cancer: PALLET Trial. Journal of Clinical Oncology](/content/review/5a973630-4e58-4bd3-b3f9-a8bcdd2026c2/source/ss-54484394/index.html) [M. Arnedos, M. Bayar, B. Cheaib, Véronique Scott, I. Bouakka, and 14 more\\ (2018).Modulation of Rb phosphorylation and antiproliferative response to palbociclib: the preoperative-palbociclib (POP) randomized clinical trial. Annals of Oncology](/content/review/5a973630-4e58-4bd3-b3f9-a8bcdd2026c2/source/ss-48364991/index.html) Download BIBDownload RISDownload TXT ## Report Status Gather sources 200 sources found Details Screen sources 10 sources included Details Extract data 80 data points extracted Details Generate report Save PDF BIBLaTeX, ZoteroRISZotero, MendeleyTXTAPA BibliographyPDFPDFDOCXMicrosoft Word Chat Got some follow-up questions? [Sign up](/content/users/auth?redirectToPath=%2Freview%2F5a973630-4e58-4bd3-b3f9-a8bcdd2026c2%2Fsource%2Fss-229690054&show=signup/index.html) or [sign in](/content/users/auth?redirectToPath=%2Freview%2F5a973630-4e58-4bd3-b3f9-a8bcdd2026c2%2Fsource%2Fss-229690054/index.html) to chat with this report. Back ## Sustained mTORC1 activity during palbociclib-induced growth arrest triggers senescence in ER+ breast cancer cells Reeja S. Maskey, F. Wang, Elyssa Lehman, Yiqun Wang, N. Emmanuel, Wenyan Zhong, G. Jin, R. Abraham, K. Arndt, Jeremy S. Myers, A. Mazurek Cell Cycle· 2020· 35 citations SourceDOI Plain textPDF Searching for PDF Unable to find PDF from source Back Study Design \- Study type: Preclinical, in vitro \- Setting: ER+ breast cancer cell lines (MCF7, T47D, CAMA1) \- Cancer type and subtype: ER+ breast cancer \- Sample size and key patient/model characteristics: Not applicable (in vitro study using cell lines) CDK4/6 Inhibitor Details \- Specific CDK4/6 inhibitor used: Palbociclib \- Dose and schedule: 500 nM \- Duration of treatment: 48 hours and various durations \- Combination therapies: Approved in combination with endocrine therapies, but not specified in the study \- Administration route and timing: Not explicitly mentioned, likely added to cell culture medium Cell Cycle Arrest Measurements \- Cell cycle phase distribution: Measured using DAPI staining and FlowJo software. \- Time points measured: 48 hours for DNA content analysis. \- Other measurements: Not explicitly mentioned in the provided quotes. Mechanism Analysis \- Rb pathway activity: Not mentioned \- Cyclin D1/CDK4/CDK6 expression and activity: Not mentioned \- Cell cycle checkpoint proteins (p16, p21, p27): Not mentioned \- Downstream signaling pathways: mTORC1 activity is sustained in CAMA1 cells during palbociclib treatment, promoting complete senescence. \- Molecular targets and biomarkers studied: Not mentioned Clinical Outcomes Not mentioned (the paper does not provide clinical efficacy outcomes related to CDK4/6 inhibitor treatment) Senescence and Cell Fate \- Senescence markers and phenotype: Not mentioned (no specific markers like SA-β-gal or SASP are discussed) \- Reversibility vs irreversibility of arrest: MCF7 and T47D cells show reversible G1-phase arrest (incomplete senescence), while CAMA1 cells undergo irreversible cell cycle arrest (complete senescence) \- Apoptosis markers: Not mentioned (no information on cleaved PARP or caspase activity) \- Autophagy activation: Not mentioned (no information on autophagy) \- Long-term cell fate outcomes: CAMA1 cells undergo complete senescence, while MCF7 and T47D cells show reversible senescent-like phenotype Resistance and Predictive Factors \- Predictive biomarkers: mTORC1 activity \- Resistance mechanisms and pathways: Sustained mTORC1 activity \- Factors associated with treatment failure: Irreversible cell cycle arrest and senescence \- Molecular subtypes or patient characteristics affecting response: ER+ breast cancer cells with sustained mTORC1 activity \- Combination strategies to overcome resistance: Inhibition of mTORC1 signaling using rapamycin or Raptor knockdown Toxicity Profile Not mentioned (the paper does not provide information on the toxicity profile of CDK4/6 inhibitor treatment) ABSTRACT Palbociclib, a selective CDK4/6 kinase inhibitor, is approved in combination with endocrine therapies for the treatment of advanced estrogen receptor positive (ER+) breast cancer. In pre-clinical cancer models, CDK4/6 inhibitors act primarily as cytostatic agents. In two commonly studied ER+ breast cancer cell lines (MCF7 and T47D), CDK4/6 inhibition drives G1-phase arrest and the acquisition of a senescent-like phenotype, both of which are reversible upon palbociclib withdrawal (incomplete senescence). Here we identify an ER+ breast cancer cell line, CAMA1, in which palbociclib treatment induces irreversible cell cycle arrest and senescence (complete senescence). In stark contrast to T47D and MCF7 cells, mTORC1 activity is not stably suppressed in CAMA1 cells during palbociclib treatment. Importantly, inhibition of mTORC1 signaling either by the mTORC1 inhibitor rapamycin or by knockdown of Raptor, a unique component of mTORC1, during palbociclib treatment of CAMA1 cells blocks the induction of complete senescence. These results indicate that sustained mTORC1 activity promotes complete senescence in ER+ breast cancer cells during CDK4/6 inhibitor-induced cell cycle arrest. Consistent with this mechanism, genetic depletion of TSC2, a negative regulator of mTORC1, in MCF7 cells resulted in sustained mTORC1 activity during palbociclib treatment and evoked a complete senescence response. These findings demonstrate that persistent mTORC1 signaling during palbociclib-induced G1 arrest is a potential liability for ER+ breast cancer cells, and suggest a strategy for novel drug combinations with palbociclib. cell culture plates, expanded further and were subjected to western blotting to confirm the genetic ablation of TSC2 in the cell population. RNA interference and viral infection For stable knockdown of RB1, RPTOR and RICTOR, a microRNA-adapted short hairpin RNA (shRNA) (based on miR-30) \[1\] against the gene of interest or a non-targeting shRNA (shCB3) were expressed using the custom 3G tetracycline regulated pTRIPZ lentiviral inducible vector (doxycycline inducible shRNA lentiviral constructs). The shRNA sequences were cloned into the XhoI/EcoRI sites of Tet-ON or Tet-OFF inducible lentiviral vectors. The XhoI-EcoRI inserts (5' to 3') for each of the shRNA, where the targeting sequence is in bold were: shRB1, CTCGAGAAGGTATATTGCTGTTGACAGTGAGCGCGCAGAGACACAAGCAACCTCATAGTG AAGCCACAGATGTATGAGGTTGCTTGTGTCTCTGCATGCCTACTGCCTCGGAATTC shRPTOR\_1673, CTCGAGAAGGTATATTGCTGTTGACAGTGAGCGCCACACTGGATTTGATAGAAAATAGTGA AGCCACAGATGTATTTTCTATCAAATCCAGTGTGATGCCTACTGCCTCGGAATTC shRPTOR\_6201, CTCGAGAAGGTATATTGCTGTTGACAGTGAGCGCCAGGTCTGATGTGAAAATTCATAGTGA AGCCACAGATGTATGAATTTTCACATCAGACCTGTTGCCTACTGCCTCGGAATTC shRICTOR\_2\_1u, CTCGAGAAGGTATATTGCTGTTGACAGTGAGCGCCAGTTTCAACTAAATGTCATATAGTGA AGCCACAGATGTATATGACATTTAGTTGAAACTGATGCCTACTGCCTCGGAATTC shRICTOR\_4782, CTCGAGAAGGTATATTGCTGTTGACAGTGAGCGCGAGTAGTTCAGTTTCAACTAATAGTGA AGCCACAGATGTATTAGTTGAAACTGAACTACTCATGCCTACTGCCTCGGAATTC shCB3, CTCGAGAAGGTATATTGCTGTTGACAGTGAGCGCTGGATGCATTTTGACGTATTATAGTGA AGCCACAGATGTATAATACGTCAAAATGCATCCAATGCCTACTGCCTCGGAATTC shRNA against RB1 was cloned into a Tet-ON inducible lentiviral backbone vector, which induces shRNA expression in the presence of doxycycline. shRNA against RPTOR and RICTOR were cloned into a Tet-OFF lentiviral backbone vector, which induces shRNA expression in the absence of doxycycline. Both vectors encode puromycin resistance. Lentiviruses were produced by cotransfection of the lentiviral backbone and Sigma-lentiviral packaging plasmids (Sigma SHP001) in the Lenti-X 293T cell line (Takara 632180). Cells were infected with virus-containing media (collected 48 h after transfection of the Lenti-X 293T cells) and selected with 2 ug ml -1 Flow cytometry For analyses of DNA content, cells treated with vehicle control or 500 nM palbociclib for 48 h were harvested and fixed with 70% ethanol at -20 o C overnight. After washing twice with 1x PBS, fixed cells were stained with 1 ug ml -1 4',6-diamidino-2-phenylindole (DAPI) in PBS for 30 min and analyzed by BD LSR II Fortessa. Percentages of the cell cycle phases were calculated using FlowJo v10 software. Western Blotting Cells treated with vehicle or palbociclib for the indicated time points were rinsed in cold PBS and lysed in ice-cold lysis buffer (50 mM Tris-Hcl pH 7.5, 150 mM sodium chloride, 1% Triton-X, 15 % glycerol) supplemented with fresh protease and phosphatase inhibitor cocktail (Thermo Scientific). Supernatants containing solubilized proteins were recovered by centrifuging at 12,000 rpm for 15 min at 4 °C and protein concentration was determined using the BCA Protein Assay (Thermo Scientific). Equal amount of protein in equal volumes were heated in NuPAGE LDS buffer with reducing agent (ThermoFisher) at 70 °C for 10 min. Protein samples were separated by SDS-PAGE on NuPAGE 4-12% Bis-Tris gels or 3-8% Tris-Acetate gels (ThermoFisher), transferred to nitrocellulose membranes, blocked with 5% nonfat dry milk (Bio-Rad) or Rockland blocking buffer (Rockland Immunochemicals, MB-070), and probed with primary antibodies diluted in either 1% BSA/TBST or Rockland blocking buffer (Rockland Immunochemicals, MB-070) overnight at 4 °C. Following washes with TBST, the membranes were incubated with IRDye 800CW-or IRDye 680RD conjugated secondary antibodies (LI-COR Biosciences) diluted in the blocking buffer containing 0.1% Tween, and signals were detected using Odyssey Infrared Imager (LI-COR). Signal intensity or quantification of protein levels were analyzed with Image Studio software version 5.2 Quantitative reverse transcription-PCR (qRT-PCR) Total RNA was isolated using RNeasy Plus Mini Kit (Qiagen) according to the manufacturer's instructions. Reverse transcription of RNA to cDNA was performed with the iScript cDNA synthesis kit (Bio-Rad #1708891). Quantitative PCR was performed in triplicate on CFX96 Real-Time System (Bio-Rad) using QuantiFast Probe PCR Master Mix (Qiagen #204354) and Taqman Assay solutions containing the assay probes and primers (Thermo Fisher Scientific). The expression level of each gene was normalized to Actb (reference gene) expression in the same sample. RNA Sequencing Cells were seeded at 100,000 cells per well into 6-well culture plates. After 24 h, cells were treated with 500 nM palbociclib for various duration. At the indicated timepoints, cells from 3 wells per cell line were lysed in their wells using RLT buffer (Qiagen) and pooled. For the vehicle-treated control, cells were lysed from log phase growing cultures alongside 2 days-palbociclib treated cells. Cell lysates were provided to Q 2 solutions (North Carolina, USA) who then purified the RNA and processed for RNA-Seq. RNA-Seq profiling was conducted by Q 2 solutions. RNAs were pair-end sequenced with read length of 2 x 100bps. Raw reads were mapped to the human hg19 reference genome using Bowtie 2 (v2.2.5) \[2\]. Expected counts and normalized expression levels of genes in transcripts per million (TPM) were generated by RSEM (v1.2.20) \[3\]. Heat map of senescenceassociated cell cycle and SASP gene expression \[4\] was performed in R using scaled (mean centered and scaled by standard deviation) TPM value. RNA-Seq data has been deposited in GEO with accession number GSE148265. Proteomics and phospho-proteomics profiling For proteomics and phospho-proteomics profiling, T47D and CAMA1 cells were plated in 15-cm dish in triplicate for each condition per cell line. The next day, cells were treated with 500 nM palbociclib or the vehicle for various timepoints. At the indicated timepoints, the cell culture medium was removed from the plates and the cells were washed twice with ice-cold PBS containing protease and phosphatase inhibitors. The plates were stored immediately at -80 o C until further analysis. For the vehicle treated control, cells were collected from log phase growing cultures alongside 6 days-palbociclib treated cells. Proteins were extracted from the cells in guanidinium chloride (GuHCl) lysis buffer (6 M GuHCl, 100 mM Tris pH 8.5, 10 mM tris(2-carboxyethyl)phosphine, 40 mM 2-chloroacetamide) with 1x protease and phosphatase inhibitors. The resulting suspensions were stored at -80 o C until they were processed, and within 2 weeks of protein extraction the suspensions were thawed and heated for 5 min at 95 °C, stood on ice for 15 min, sonicated (with Branson probe sonifier output 3-4, 50% duty cycle (15s on 15s off), three times), heated again (95 °C for 5 min), and followed by centrifugation for 20 min at 16,000g (4 °C). The supernatant was removed to a clean tube and protein concentration was measured by Bradford protein assay. Removed 0.8 mg protein to a new clean Eppendorf tube. Lys-C (Promega) was added at a ratio of 1:100 Lys-C:total protein. The digestion was performed at room temperature for 4 h. The digestion solution was diluted by 10 fold with 100 mM Tris, pH 8.5, and trypsin (1:25 weight ratio of trypsin:proteins) was added. The digestion was continued at 37 o C for overnight. The next day, a second portion of trypsin (1:35 of trypsin:proteins) was added, and the resulting solution was incubated for an additional 4 h at 37 o C. At the end of digestion, 20% TFA was added to get final concentration of 0.7% TFA to stop the digestion. The resulting digest solution incubated on ice for 15 min, after which it was centrifuged for 60 min at 3,600 g at 4 o C, and the supernatant was collected. The resulting peptide mixture was concentrated and desalted using reversed-phase 100 mg Sep-Pak tC18 Cartridge (Waters). The desalted peptides were dried by vacuum centrifugation and re-dissolved in 100 mM TEAB and labeled with TMT-10 plex (Thermo Fisher). After TMT labeling, differently labeled samples were immediately combined for multiplexed acquisition. For total proteomics, 0.5 mg of the combined digest was removed and dried by vacuum centrifugation, and then re-suspended in 20 mM NH3H2O/2% acetonitrile (v:v) for off-line high pH RPLC using BEH C18 column (Waters) to collect 96 fractions. These fractions were pooled to 32 fractions, dried by vacuum centrifugation, and re-suspended in 0.1% TFA/2% acetonitrile (v:v) for LC-MS/MS analysis. For phosphoproteomics, 7.5 mg of the pooled digest was resuspended in 20 mM NH3H2O/2% acetonitrile (v:v) for off-line high pH RPLC using BEH C18 column to collect 96 fractions. The fractions were pooled to 10 fractions and dried by vacuum centrifugation. A Titansphere ™ Phos-TiO Spin-tip TiO2 Bulk tip with volume 3mg/200uL (GL Sciences) was used to enrich phosphopeptides. Phosphopeptides were eluted from TiO2 tip and desalted with a combination of GL-Tip SDB and GC (GL Sciences). The final elute from the stage-tips was dried with vacuum centrifugation and re-suspended in 0.3% TFA/2% acetonitrile (v:v) for LC-MS/MS analysis. Each sample was acquired on Thermo Scientific™ Q Exactive™ Hybrid Quadrupole-Orbitrap Mass Spectrometer fitted with a Dionex nano liquid chromatography and EASY-Spray™ Ion source. The tryptic digest or enriched phosphopeptides was loaded on 100 μm × 2 cm C18 trap column (Acclaim PepMap 100, Thermo Fisher Scientific, Inc.). Peptide separation was conducted via nano-LC using a 75 m x 50 cm PepMap C18 EASY-Spray column (3 m, 100 Å particles, Thermo Scientific, Inc.). Mobile phase A was water containing 0.1% formic acid and mobile phase B was acetonitrile containing 0.1% formic acid. The gradient was comprised of mobile phase B increased from 2 to 7% in 5 min, from 7% to 30% over 110 min, from 30 to 50% over 20 min, from 50% to 80% in 2 min, and a hold at 80% B for the last 6 min, all at a fixed flow rate of 300 nl/min in an Ultimate 3000 RSLCnano system (Thermo Fisher Scientific, Inc.). Q Exactive was operated with data dependent top 10 acquisition method and its parameters were as follows: resolution 70,000 at m/z 200 for MS1 with scan range of 300-1650 m/z for total proteomics and 375-1500 m/z for phosphoproteomics, a predictive AGC target of 3 x 10 6 and maximum injection time 200 ms for total proteomics and 250 ms for phosphoproteomics; 35,500 at m/z 200 for dd-MS2 with a predictive AGC target of 2 x 10 5 , isolation width 1.2 Th, maximum injection time 120 ms for total proteomics and 200 ms for phosphoproteomics , NCE of 32, 30s dynamic exclusion and underfill ratio 10%. ProteomeDiscover 2.2 was used for protein identification and quantification and ProteomeDiscover 2.3 for phosphopeptide identification and quantification. Peptides were identified and quantified for TMT-based quantification from raw mass spectrometric files. Database search was performed using the SEQUEST search engine \[5\] against human Uniport database (42,096 entries, Jan. 18, 2017 version) and a list of common contaminants at a false discovery rate (FDR) of 1% on peptide spectrum match and protein levels. SEQUEST search parameters for peptide identification were set as follows: tolerance of 10 ppm for precursor ions and 0.02 Da for fragmentation ions; digestion was set to specific "Trypsin/P" allowing max missed cleavage events of 2. Oxidation of methionine, protein N-terminal acetylation and deamidation (N) were set as variable modifications. For phosphoproteomics, phosphorylation of STY was also set as variable modifications. Carboxyamidomethylation of cysteines was specified as a fixed modification for all searches. TMT-labeled N-terminus and TMT-labeled Lysine were set as a variable modification in one SEQUEST search and as a fixed modification in another SEQUEST search, respectively. Maximum number of modifications per peptide was set as 5. Minimal required peptide length was 7 amino acid. Confidently identified proteins required at least two peptides with 1 unique peptide at a false discovery rate (FDR) ≤ 0.1% on the peptide spectrum match and protein group level. All proteins "Reverse", "Potential contaminant" and "Razor + unique peptides = 1" were removed. Proteins and phosphopeptides were quantified by scaled abundance of TMT-reporter ions, which is relative quantification for same protein or phosphopeptide across samples. Scaled abundances of proteins or phosphopeptides were further analyzed in Perseus (version: 1.6.0.7) \[6\] for statistical analysis. Scaled abundance of phosphopeptides were corrected with changes of protein abundance. 6317 proteins passed an ANOVA multiple sample tests with Benjamini-Hochberg FDR ≤ 0.05. Hierarchical clustering of significant changed proteins or phosphopeptides were performed using Euclidean distance and the complete linkage clustering method. Proteins and phosphopeptides that are significantly changed were obtained by pairwise comparison of the log2 transformed Scaled Abundance value of the treatment sample to its corresponding control using a student T-test. For proteomics, proteins with student T-test FDR (Benjamini-Hochberg) ≤ 0.05 and log2 fold change ≥ 0.38 or ≤ -0.38 were selected for further pathway and functional enrichment analysis performed in Perseus using Fisher Exact Test against KEGG pathway with the multiple test of Benjamini-Hochberg FDR ≤ 0.001. For phosphoproteomics, phosphopeptides changed significantly were filtered with log2 fold change ≥ 0.58 or ≤ -0.58 for phosphopeptides which were detected in single replicate and student T-test FDR (Benjamini-Hochberg) ≤ 0.05 and log2 fold change ≥ 0.58 or ≤ -0.58 for phosphopeptides that were detected in 2 or 3 replicates, similar to the reported analysis \[7\]. We also included the phosphopeptides which were detected in 2 or 3 replicates with the average of log2 fold change ≥ 0.58 or ≤ -0.58 and student T test FDR (Benjamini-Hochberg) > 0.05 if log2 fold change between the smallest value in the palbociclib-treated sample and the biggest value in the control sample > 0.38 or if log2 fold change between the biggest value in the palbociclib-treated sample and the smallest value in the control sample < -0.38, respectively. Pathway and functional enrichment analysis at phosphoproteome level were using Fisher Exact Test against KEGG pathway with Benjamini-Hochberg FDR ≤ 0.02 in Perseus. For proteomics analysis of MCF7 and T47D cells treated with palbociclib for 1, 3 and 6 days, cells were detached with CellStripper (Mediatech) and washed with PBS. Cells were fractionated into membrane and soluble fractions using sodium carbonate extraction buffer (sodium carbonate adjusted to pH 11.5 with 1x Halt protease and phosphatase inhibitors (Thermo Fisher Scientific)). Cell suspension was then adjusted to final concentration of 2 mM MgCl2 and pH 8 by the addition of Tris-HCl pH 7.0. Universal Nuclease (Thermo Fisher Scientific) was used to reduce viscosity associated with denatured genomic DNA by digestion for 30 min on ice. Following digestion, membrane fraction was isolated by centrifugation at 20,000 g for 30 min. The resulting membrane fraction (pellet) was solubilized using RIPA buffer (25 mM Tris-HCl pH 7.6, 150 mM NaCl, 1% SDS, 1% sodium deoxycholate, 1% NP-40 and 1x Halt Protease Inhibitor (Thermo Fisher Scientific)) to solubilize membrane proteins, whereas the soluble fraction was used directly for subsequent processing. Protein concentration was determined by the Pierce BCA assay according to manufacturer's directions (Thermo Fisher Scientific). 50 g of proteins was added to Microcon-10 KDa centrifugal filter (Millipore), washed 3X with 8 M urea to remove detergents. Proteins were reduced with freshly prepared 5 mM DTT for 1 h and alkylated with freshly prepared 10 mM iodoacetamide (Sigma, A3221) in the dark for 45 min. Samples were then washed three times with freshly prepared 25 mM ammonium bicarbonate buffer and digested with mass spec grade trypsin/LysC (Promega, V5071) with protein:enzyme at a 25:1 weight ratio overnight at 30 o C. Following digestion, the peptides were captured by centrifugation at 15,000 g for 20 min, followed by the addition of 10% formic acid to a final concentration of 0.25% formic acid. Resulting peptides were fractionated by nano-LC using a custom fabricated C18 column, and detected by nano-electrospray ionization on Thermo Scientific LTQ Orbitrap Velos operating at 60,000 resolution over a mass range of 300-2000 Da in parallel scanning mode with dynamic exclusion, where the top 20 most intense ions were selected for tandem mass spectrometry fragmentation in the ion trap. For soluble and membrane fractions, peptides were identified and quantified for label-free protein quantification (LFQ) from raw mass spectrometric files using MaxQuant software (version: 1.6.1.0) \[8\]. Database searching was performed in MaxQuant using the Andromeda search engine \[5\] against the human Uniprot database (42,096 entries, January 2017 version). Andromeda search parameters for protein identification were set as follows: tolerance of 20 ppm for the first search peptide, 4.5 ppm for maximum mass tolerance for the precursor ions after non-linear recalibration and 20 ppm for matched fragmentation spectra; digestion was set to specific "Trypsin/P" allowing max missed cleavage events of two. Oxidation of methionine and protein N-terminal acetylation were set as variable modifications. Carboxyamidomethylation of cysteines was specified as a fixed modification. A total of three modifications were allowed per peptide. Minimum required peptide length was seven amino acids. MaxQuant LFQ "match between run" option was enabled with a match time window of 0.7 minutes after retention time alignment. "Requires MS/MS for label-free quantification (LFQ) comparisons" was not enabled to allow maximum MS peak features. Confidently identified proteins were required to have a minimum of two matched peptides with one peptide being uniquely matched at a false discovery rate (FDR) of less than 1%. Proteins were quantified by delayed normalization computed in MaxQuant's label-free quantification option \[9\]. LFQ intensity data by protein group was further analyzed in Perseus (version: 1.6.0.7). All proteins "identified by site", "reverse", and contaminants were removed. LFQ intensity value was log2 transformed and the resulting data matrix was further filtered requiring minimal values of ≥ 75% in at least one sample. Proteins that are significantly up-or down-regulated in palbociclib-treated MCF7 or T47D cells were obtained by pairwise comparison of the log2 transformed LFQ value of palbociclib treated sample from membrane fraction or soluble fraction to control sample using student t-test within Perseus. Proteins with FDR (Benjamini-Hochberg) ≤ 0.05 and log2 fold change ≥ 0.58 or ≤ -0.58 were selected for further pathway and function enrichment analysis. If proteins were detected in both membrane and soluble fractions, higher LFQ values of the proteins will be kept. Pathway, function enrichment and network analysis were performed with WEB-based GEne SeT AnaLysis Toolkit, Over-representation Analysis (ORA) \[10\] using KEGG pathway with the multiple test of Benjamin-Hochberg FDR ≤ 0.01. annex mzML files were generated from raw data files of TMT-based proteomics and phosphoproteomics using MSConvert \[11\]. Proteomics and phospho-proteomics data of CAMA1 and T47D cells treated with palbociclib for 1, 6, 10 and 14 days have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD019026. Similarly, proteomics data of MCF7 and T47D cells treated with palbociclib for 1, 3 and 6 days have been deposited with the dataset identifier PXD018607. Failed to load PDF: StripeM-Inner Paper sources Abstract screening pilot Abstract screening results Extraction pilot Extraction results Research report * * * Modify setup