Phenotyping Hepatic Immune-Related Adverse Events in the Setting of Immune Checkpoint Inhibitor Therapy.

PURPOSE: We present and validate a rule-based algorithm for the detection of moderate to severe liver-related immune-related adverse events (irAEs) in a real-world patient cohort. The algorithm can be applied to studies of irAEs in large data sets. METHODS: We developed a set of criteria to define hepatic irAEs. The criteria include: the temporality of elevated laboratory measurements in the first 2-14 weeks of immune checkpoint inhibitor (ICI) treatment, steroid intervention within 2 weeks of the onset of elevated laboratory measurements, and intervention with a duration of at least 2 weeks. These criteria are based on the kinetics of patients who experienced moderate to severe hepatotoxicity (Common Terminology Criteria for Adverse Events grades 2-4). We applied these criteria to a retrospective cohort of 682 patients diagnosed with hepatocellular carcinoma and treated with ICI. All patients were required to have baseline laboratory measurements before and after the initiation of ICI. RESULTS: A set of 63 equally sampled patients were reviewed by two blinded, clinical adjudicators. Disagreements were reviewed and consensus was taken to be the ground truth. Of these, 25 patients with irAEs were identified, 16 were determined to be hepatic irAEs, 36 patients were nonadverse events, and two patients were of indeterminant status. Reviewers agreed in 44 of 63 patients, including 19 patients with irAEs (0.70 concordance, Fleiss' kappa: 0.43). By comparison, the algorithm achieved a sensitivity and specificity of identifying hepatic irAEs of 0.63 and 0.81, respectively, with a test efficiency (percent correctly classified) of 0.78 and outcome-weighted F1 score of 0.74. CONCLUSION: The algorithm achieves greater concordance with the ground truth than either individual clinical adjudicator for the detection of irAEs.

Baseline correlates of frailty and its association with survival in United States veterans with acute myeloid leukemia.

Frailty is an important construct to measure in acute myeloid leukemia (AML). We used the Veterans Affairs Frailty Index (VA-FI) - calculated using readily available data within the VA's electronic health records - to measure frailty in U.S. veterans with AML. Of the 1166 newly diagnosed and treated veterans with AML between 2012 and 2022, 722 (62%) veterans with AML were classified as frail (VA-FI > 0.2). At a median follow-up of 252.5 days, moderate-severely frail veterans had significantly worse survival than mildly frail, and non-frail veterans (median survival 179 vs. 306 vs. 417 days, p < .001). Increasing VA-FI severity was associated with higher mortality. A model with VA-FI in addition to the European LeukemiaNet (ELN) risk classification and other covariates statistically outperformed a model containing the ELN risk and other covariates alone (p < .001). These findings support the VA-FI as a tool to expand frailty measurement in research and clinical practice for informing prognosis in veterans with AML.

Machine learning-based natural language processing to extract PD-L1 expression levels from clinical notes.

Introduction: PD-L1 expression is used to determine oncology patients' response to and eligibility for immunologic treatments; however, PD-L1 expression status often only exists in unstructured clinical notes, limiting ability to use it in population-level studies. Methods: We developed and evaluated a machine learning based natural language processing (NLP) tool to extract PD-L1 expression values from the nationwide Veterans Affairs electronic health record system. Results: The model demonstrated strong evaluation performance across multiple levels of label granularity. Mean precision of the overall PD-L1 positive label was 0.859 (sd, 0.039), recall 0.994 (sd, 0.013), and F1 0.921 (0.024). When a numeric PD-L1 value was identified, the mean absolute error of the value was 0.537 on a scale of 0 to 100. Conclusion: We presented an accurate NLP method for deriving PD-L1 status from clinical notes. By reducing the time and manual effort needed to review medical records, our work will enable future population-level studies in cancer immunotherapy.

Positive affect and resilience in tertiary education students.

Mental illnesses are the greatest health problems faced by younger people. As a group, tertiary education students demonstrate higher levels of distress than their age matched peers who are not tertiary students, making them an at-risk group for the development of psychopathology. Therefore, this study investigates existing theories of resilience in order to determine how it may be promoted in tertiary education students. Data relating to affect, depression, anxiety, distress, and resilience were collected from 1072 tertiary education students during the COVID-19 pandemic. The results of this study found that positive affect was responsible for approximately 25% of the variance in depressive symptoms but less than 10% of the variance in symptoms of anxiety in tertiary students. The results further showed that positive affect was responsible for 21% of variance in overall distress and the 15% of variance in resilience. The findings of this study suggest that positive affect is more closely associated with symptoms of depression than with symptoms of anxiety in tertiary students. The results further suggest that positive affect may be a useful tool for relieving symptoms of depression and overall distress, and improving levels of resilience in this population.

Distress of tertiary education students in Australia during the COVID-19 pandemic.

OBJECTIVE: This project sought to characterize levels of distress in Australian tertiary education students during the COVID-19 pandemic. METHODS: Advertisements were placed on multiple participant recruitment and student run websites associated with various tertiary institutions. Level of overall distress was assessed with the K-10 so that comparisons could be made with previous research. A total of 1072 tertiary education students 18 years or older participated in the study. RESULTS: 70.9% of tertiary education students studying in Australia displayed elevated levels of psychological distress during the pandemic, with 23.01% of the sample reporting extreme levels of distress. CONCLUSIONS: More tertiary education students experienced severe distress during the COVID-19 pandemic than adults in the general population, as well as before the pandemic. IMPLICATIONS: Services are needed to help tertiary education students cope with elevated levels of distress associated during the COVID-19 pandemic.

Prognostic value of the veterans affairs frailty index in older patients with non-small cell lung cancer.

BACKGROUND: Older patients with non-small cell lung cancer (NSCLC) are a heterogeneous population with varying degrees of frailty. An electronic frailty index such as the Veterans Affairs Frailty Index (VA-FI) can potentially help identify vulnerable patients at high risk of poor outcomes. METHODS: NSCLC patients ≥65 years old and diagnosed in 2002-2017 were identified using the VA Central Cancer Registry. The VA-FI was calculated using administrative codes from VA electronic health records data linked with Medicare and Medicaid data. We assessed associations between the VA-FI and times to mortality, hospitalization, and emergency room (ER) visit following diagnosis by Kaplan-Meier analysis and multivariable stratified Cox models. We also evaluated the change in discrimination and calibration of reference prognostic models after adding VA-FI. RESULTS: We identified a cohort of 42,204 older NSCLC VA patients, in which 55.5% were classified as frail (VA-FI >0.2). After adjustment, there was a strong association between VA-FI and the risk of mortality (HR = 1.23 for an increase of four deficits or, equivalently, an increase of 0.129 on VA-FI, p < 0.001), hospitalization (HR = 1.16 for four deficits, p < 0.001), and ER visit (HR = 1.18 for four deficits, p < 0.001). Adding VA-FI to baseline prognostic models led to statistically significant improvements in time-dependent area under curves and did not have a strong impact on calibration. CONCLUSION: Older NSCLC patients with higher VA-FI have significantly elevated risks of mortality, hospitalizations, and ER visits following diagnosis. An electronic frailty index can serve as an accessible tool to identify patients with vulnerabilities to inform clinical care and research.

A cancer graph: a lung cancer property graph database in Neo4j.

OBJECTIVES: A novel graph data model of non-small cell lung cancer clinical and genomic data has been constructed with two aims: (1) provide a suitable model for facilitating graph analytics within the Neo4j framework or through tools which can interact through existing Neo4j APIs; and (2) provide a base model extensible to other cancer types and additional datasets such as those derived from electronic health records and other real world sources. DATA DESCRIPTION: Clinical and genomic data integrated with a novel property graph database schema from publicly available datasets and analyses based on The Cancer Genome Atlas lung cancer datasets augmented by with subgraphs patient-patient social network from similarity and correlation as well as individual based biological networks.

Association of COVID-19 Vaccination With SARS-CoV-2 Infection in Patients With Cancer: A US Nationwide Veterans Affairs Study.

Importance: Patients with cancer are at increased risk for severe COVID-19, but it is unknown whether SARS-CoV-2 vaccination is effective for them. Objective: To determine the association between SARS-CoV-2 vaccination and SARS-CoV-2 infections among a population of Veterans Affairs (VA) patients with cancer. Design, Setting, and Participants: Retrospective, multicenter, nationwide cohort study of SARS-CoV-2 vaccination and infection among patients in the VA health care system from December 15, 2020, to May 4, 2021. All adults with solid tumors or hematologic cancer who received systemic cancer-directed therapy from August 15, 2010, to May 4, 2021, and were alive and without a documented SARS-CoV-2 positive result as of December 15, 2020, were eligible for inclusion. Each day between December 15, 2020, and May 4, 2021, newly vaccinated patients were matched 1:1 with unvaccinated or not yet vaccinated controls based on age, race and ethnicity, VA facility, rurality of home address, cancer type, and treatment type/timing. Exposures: Receipt of a SARS-CoV-2 vaccine. Main Outcomes and Measures: The primary outcome was documented SARS-CoV-2 infection. A proxy for vaccine effectiveness was defined as 1 minus the risk ratio of SARS-CoV-2 infection for vaccinated individuals compared with unvaccinated controls. Results: A total of 184 485 patients met eligibility criteria, and 113 796 were vaccinated. Of these, 29 152 vaccinated patients (median [IQR] age, 74.1 [70.2-79.3] years; 95% were men; 71% were non-Hispanic White individuals) were matched 1:1 to unvaccinated or not yet vaccinated controls. As of a median 47 days of follow-up, 436 SARS-CoV-2 infections were detected in the matched cohort (161 infections in vaccinated patients vs 275 in unvaccinated patients). There were 17 COVID-19-related deaths in the vaccinated group vs 27 COVID-19-related deaths in the unvaccinated group. Overall vaccine effectiveness in the matched cohort was 58% (95% CI, 39% to 72%) starting 14 days after the second dose. Patients who received chemotherapy within 3 months prior to the first vaccination dose were estimated to have a vaccine effectiveness of 57% (95% CI, -23% to 90%) starting 14 days after the second dose vs 76% (95% CI, 50% to 91%) for those receiving endocrine therapy and 85% (95% CI, 29% to 100%) for those who had not received systemic therapy for at least 6 months prior. Conclusions and Relevance: In this cohort study, COVID-19 vaccination was associated with lower SARS-CoV-2 infection rates in patients with cancer. Some immunosuppressed subgroups may remain at early risk for COVID-19 despite vaccination, and consideration should be given to additional risk reduction strategies, such as serologic testing for vaccine response and a third vaccine dose to optimize outcomes.

Multi-scale Pan-cancer Integrative Analyses Identify the STAT3-VSIR Axis as a Key Immunosuppressive Mechanism in Head and Neck Cancer.

PURPOSE: VSIR is a novel immune checkpoint protein whose expression on tumor cells across cancers remains largely uncharacterized. Here we purposed to decode the pan-cancer biologic and clinical significance of VSIR overexpression in the tumor compartment. EXPERIMENTAL DESIGN: We performed multi-omics integrative analyses of 9,735 tumor samples to identify cancers with non-leukocytic expression of VSIR (VSIR High), followed by association with overall survival and immune cell infiltration levels. Orthogonal assessments of VSIR protein expression and lymphocytic infiltration were performed using quantitative immunofluorescence (QIF). RESULTS: Integrative modeling identified a subset of cancer types as being enriched for VSIR High tumors. VSIR High tumors were associated with significantly poorer overall survival in immunogenic ovarian serous adenocarcinoma (SA) and oral cavity squamous cell carcinoma (SCC). QIF assessments in an independent validation cohort confirmed overexpression of VSIR as being associated with poorer overall survival within immunogenic oral cavity SCC. VSIR overexpression was associated with lower CD4 helper T-cell infiltration in both ovarian SA and oral cavity SCC, but did not impact CD8 T-cell infiltration. VSIR overexpressing tumors in both cancer types exhibited significantly higher STAT3 signaling activity. Pharmacologic inhibition of STAT3 signaling resulted in dose-dependent reduction of VSIR expression in ovarian SA and oral cavity SCC cells. CONCLUSIONS: The STAT3-VSIR axis is a potentially significant immunomodulatory mechanism in oral cavity and ovarian cancers, whose activation is associated with poorer survival and an immune microenvironment marked by decreased CD4 helper T-cell activity. The role of VSIR as a tumor-intrinsic modulator of resistance to immunotherapy warrants further exploration.

Evaluating the impact of age on immune checkpoint therapy biomarkers.

Both tumors and aging alter the immune landscape of tissues. These interactions may play an important role in tumor progression among elderly patients and may suggest considerations for patient care. We leverage large-scale genomic and clinical databases to perform comprehensive comparative analysis of molecular and cellular markers of immune checkpoint blockade (ICB) response with patient age. These analyses demonstrate that aging is associated with increased tumor mutational burden, increased expression and decreased promoter methylation of immune checkpoint genes, and increased interferon gamma signaling in older patients in many cancer types studied, all of which are expected to promote ICB efficacy. Concurrently, we observe age-related alterations that might be expected to reduce ICB efficacy, such as decreases in T cell receptor diversity. Altogether, these changes suggest the capacity for robust ICB response in many older patients, which may warrant large-scale prospective study on ICB therapies among patients of advanced age.

Prevalence and Outcome of COVID-19 Infection in Cancer Patients: A National Veterans Affairs Study.

BACKGROUND: Emerging data suggest variability in susceptibility and outcome to coronavirus disease 2019 (COVID-19) infection. Identifying risk factors associated with infection and outcomes in cancer patients is necessary to develop healthcare recommendations. METHODS: We analyzed electronic health records of the US Veterans Affairs Healthcare System and assessed the prevalence of COVID-19 infection in cancer patients. We evaluated the proportion of cancer patients tested for COVID-19 who were positive, as well as outcome attributable to COVID-19, and stratified by clinical characteristics including demographics, comorbidities, cancer treatment, and cancer type. All statistical tests are 2-sided. RESULTS: Of 22 914 cancer patients tested for COVID-19, 1794 (7.8%) were positive. The prevalence of COVID-19 was similar across age. Higher prevalence was observed in African American (15.0%) compared with White (5.5%; P < .001) and in patients with hematologic malignancy compared with those with solid tumors (10.9% vs 7.8%; P < .001). Conversely, prevalence was lower in current smokers and patients who recently received cancer therapy (<6 months). The COVID-19-attributable mortality was 10.9%. Higher attributable mortality rates were observed in older patients, those with higher Charlson comorbidity score, and in certain cancer types. Recent (<6 months) or past treatment did not influence attributable mortality. Importantly, African American patients had 3.5-fold higher COVID-19-attributable hospitalization; however, they had similar attributable mortality as White patients. CONCLUSION: Preexistence of cancer affects both susceptibility to COVID-19 infection and eventual outcome. The overall COVID-19-attributable mortality in cancer patients is affected by age, comorbidity, and specific cancer types; however, race or recent treatment including immunotherapy do not impact outcome.

Real-World Outcomes for Patients Treated With Immune Checkpoint Inhibitors in the Veterans Affairs System.

PURPOSE: Increasingly broad patient groups are being treated with immune checkpoint inhibitors (ICIs) in clinical practice, but few studies have assessed their usage and outcomes in large, comprehensive real-world cohorts. We identified patients who received ICIs in the Veterans Affairs (VA) health care system and described patient characteristics and survival outcomes across multiple indications. METHODS: We conducted a retrospective analysis using electronic health record data from VA facilities nationwide. Overall survival (OS) from time of ICI initiation for key indications was estimated by Kaplan-Meier. We also stratified OS by frailty status, as defined by a surrogate index developed in VA data. For select indications, we further compared outcomes to historic and concurrent control patients treated with standard-of-care regimens at the VA. RESULTS: We identified 11,888 patients who were treated with ICIs and determined the cancer type and indication for which they were treated. The cohort is enriched for patient groups that are under-represented in pivotal clinical trials (PCTs), including older, non-White, and/or higher disease burdened patients. Generally, OS observed in the VA cohort is lower than that reported in PCTs. After stratifying VA patients by frailty status, OS among nonfrail patients is more similar to OS reported in PCTs for some indications. Compared with internal VA control cohorts, patients treated with ICIs generally exhibited longer OS for all indications considered. CONCLUSION: This study describes ICI outcomes across multiple tumor types in a real-world population at the VA. For most indications, real-world survival outcomes are observed to be lower than those reported in PCTs, but patients receiving ICIs still achieve longer survival relative to patients receiving standard of care.

External validation of a prognostic model for mortality among patients with non-small-cell lung cancer using the Veterans Precision Oncology Data Commons.

BACKGROUND: There is wide interest in developing prognostic models in non-small-cell lung cancer (NSCLC) due to the heterogeneity of the disease. Models developed at other healthcare institutions may not be directly applicable for patients treated at the Department of Veterans Affairs (VA). External validation of a candidate prognostic model among VA patients would be crucial before it can be implemented to aid clinical decision-making. METHODS: A prognostic model for mortality developed in the Military Health System (MHS) was applied to data from the VA Precision Oncology Data Repository (VA-PODR), which is available to researchers inside and outside the VA at the Veterans Precision Oncology Data Commons (VPODC). Measures of discrimination and calibration were calculated for the MHS model. The MHS model was also refitted in VA-PODR data using the same risk factors to compare the effect of specific factors and predictive performance when the model is developed using VA data. RESULTS: Time-dependent AUC of the MHS prognostic model was 0.788, 0.806, 0.780, and 0.779 for predicting survival at 1, 2, 3, and 5 years following diagnosis, respectively. Significant discrepancies were found between predicted and observed rates of survival, particularly for later years. When the model is refit in VA-PODR data, it achieved cross-validated AUCs of 0.739, 0.773, 0.769, and 0.807 at the same time points, and discrepancies between predicted and observed survival were reduced. CONCLUSIONS: Validation of the MHS prognostic model in VA-PODR demonstrates that its discrimination remains strong when applied to VA patients. Nevertheless, further calibration to VA data may be needed to improve its risk estimation performance. This study highlights the utility of VA-PODR and the VPODC as a national resource for developing analytic tools that are well adapted to the Veteran population.

The Veterans Precision Oncology Data Commons: Transforming VA data into a national resource for research in precision oncology.

The Department of Veterans Affairs (VA) has a strong track record providing high-quality, evidence-based care to cancer patients. In order to accelerate discoveries that will further improve care for Veterans with cancer, the VA has partnered with the Center for Translational Data Science at the University of Chicago and the Open Commons Consortium to establish a data sharing platform, the Veterans Precision Oncology Data Commons (VPODC). The VPODC makes clinical, genomic, and imaging data from the VA available to the research community at large. In this paper, we detail our motivation for data sharing, describe the VPODC, and outline our collaboration model. By transforming VA data into a national resource for research in precision oncology, the VPODC seeks to foster innovation through collaboration and resource sharing that will ultimately lead to improved care for Veterans with cancer.

CUDC-907 in relapsed/refractory diffuse large B-cell lymphoma, including patients with MYC-alterations: results from an expanded phase I trial.

CUDC-907 is a first-in-class, oral small molecule inhibitor of both HDAC (class I and II) and PI3K (class Iα, ß, and δ) enzymes, with demonstrated anti-tumor activity in multiple pre-clinical models, including MYC-driven ones. In this report, we present the safety and preliminary activity results of CUDC-907, with and without rituximab, in patients with relapsed/refractory diffuse large B-cell lymphoma (DLBCL), with a particular focus on those with MYC-altered disease. Thirty-seven DLBCL patients were enrolled, 14 with confirmed MYC-altered disease. Twenty-five patients received monotherapy treatment, and 12 received the combination of CUDC-907 with rituximab. CUDC-907 monotherapy and combination demonstrated similar safety profiles consisting primarily of Grade 1/2 hematologic and gastrointestinal events. The most frequently reported Grade ≥3 treatment-related events were thrombocytopenia, neutropenia, diarrhea, fatigue, and anemia. Eleven responses (5 complete responses and 6 partial responses) were reported, for a response rate of 37% (11 out of 30) in evaluable patients [30% (11 out of 37) including all patients]. The objective response rate in evaluable MYC-altered DLBCL patients was 64% (7 out of 11; 4 complete responses and 3 partial responses), while it was 29% (2 out of 7) in MYC unaltered, and 17% (2 out of 12) in those with unknown MYC status. Median duration of response was 11.2 months overall; 13.6 months in MYC-altered patients, 6.0 months in MYC unaltered, and 7.8 months in those with MYC status unknown. The tolerable safety profile and encouraging evidence of durable anti-tumor activity, particularly in MYC-altered patients, support the continued development of CUDC-907 in these populations of high unmet need. (clinicaltrials.gov identifier: 01742988).

New Cancer Immunotherapy Agents in Development: a report from an associated program of the 31stAnnual Meeting of the Society for Immunotherapy of Cancer, 2016.

This report is a summary of 'New Cancer Immunotherapy Agents in Development' program, which took place in association with the 31st Annual Meeting of the Society for Immunotherapy of Cancer (SITC), on November 9, 2016 in National Harbor, Maryland. Presenters gave brief overviews of emerging clinical and pre-clinical immune-based agents and combinations, before participating in an extended panel discussion with multidisciplinary leaders, including members of the FDA, leading academic institutions and industrial drug developers, to consider topics relevant to the future of cancer immunotherapy.

Dual HDAC and PI3K Inhibitor CUDC-907 Downregulates MYC and Suppresses Growth of MYC-dependent Cancers.

Upregulation of MYC is a common driver event in human cancers, and some tumors depend on MYC to maintain transcriptional programs that promote cell growth and proliferation. Preclinical studies have suggested that individually targeting upstream regulators of MYC, such as histone deacetylases (HDAC) and phosphoinositide 3-kinases (PI3K), can reduce MYC protein levels and suppress the growth of MYC-driven cancers. Synergy between HDAC and PI3K inhibition in inducing cancer cell death has also been reported, but the involvement of MYC regulation is unclear. In this study, we demonstrated that HDAC and PI3K inhibition synergistically downregulates MYC protein levels and induces apoptosis in "double-hit" (DH) diffuse large B-cell lymphoma (DLBCL) cells. Furthermore, CUDC-907, a small-molecule dual-acting inhibitor of both class I and II HDACs and class I PI3Ks, effectively suppresses the growth and survival of MYC-altered or MYC-dependent cancer cells, such as DH DLBCL and BRD-NUT fusion-positive NUT midline carcinoma (NMC) cells, and MYC protein downregulation is an early event induced by CUDC-907 treatment. Consistently, the antitumor activity of CUDC-907 against multiple MYC-driven cancer types was also demonstrated in animal models, including DLBCL and NMC xenograft models, Myc transgenic tumor syngeneic models, and MYC-amplified solid tumor patient-derived xenograft (PDX) models. Our findings suggest that dual function HDAC and PI3K inhibitor CUDC-907 is an effective agent targeting MYC and thus may be developed as potential therapy for MYC-dependent cancers. Mol Cancer Ther; 16(2); 285-99. ©2016 AACR.

Estrogen Drives Cellular Transformation and Mutagenesis in Cells Expressing the Breast Cancer-Associated R438W DNA Polymerase Lambda Protein.

Repair of DNA damage is critical for maintaining the genomic integrity of cells. DNA polymerase lambda (POLL/Pol λ) is suggested to function in base excision repair (BER) and nonhomologous end-joining (NHEJ), and is likely to play a role in damage tolerance at the replication fork. Here, using next-generation sequencing, it was discovered that the POLL rs3730477 single-nucleotide polymorphism (SNP) encoding R438W Pol λ was significantly enriched in the germlines of breast cancer patients. Expression of R438W Pol λ in human breast epithelial cells induces cellular transformation and chromosomal aberrations. The role of estrogen was assessed as it is commonly used in hormone replacement therapies and is a known breast cancer risk factor. Interestingly, the combination of estrogen treatment and the expression of the R438W Pol λ SNP drastically accelerated the rate of transformation. Estrogen exposure produces 8-oxoguanine lesions that persist in cells expressing R438W Pol λ compared with wild-type (WT) Pol λ-expressing cells. Unlike WT Pol λ, which performs error-free bypass of 8-oxoguanine lesions, expression of R438W Pol λ leads to an increase in mutagenesis and replicative stress in cells treated with estrogen. Together, these data suggest that individuals who carry the rs3730477 POLL germline variant have an increased risk of estrogen-associated breast cancer. IMPLICATIONS: The Pol λ R438W mutation can serve as a biomarker to predict cancer risk and implicates that treatment with estrogen in individuals with this mutation may further increase their risk of breast cancer. Mol Cancer Res; 14(11); 1068-77. ©2016 AACR.

Overcoming Therapeutic Resistance in HER2-Positive Breast Cancers with CDK4/6 Inhibitors.

Using transgenic mouse models, cell line-based functional studies, and clinical specimens, we show that cyclin D1/CDK4 mediate resistance to targeted therapy for HER2-positive breast cancer. This is overcome using CDK4/6 inhibitors. Inhibition of CDK4/6 not only suppresses Rb phosphorylation, but also reduces TSC2 phosphorylation and thus partially attenuates mTORC1 activity. This relieves feedback inhibition of upstream EGFR family kinases, resensitizing tumors to EGFR/HER2 blockade. Consequently, dual inhibition of EGFR/HER2 and CDK4/6 invokes a more potent suppression of TSC2 phosphorylation and hence mTORC1/S6K/S6RP activity. The suppression of both Rb and S6RP enhances G1 arrest and a phenotype resembling cellular senescence. In vivo, CDK4/6 inhibitors sensitize patient-derived xenograft tumors to HER2-targeted therapies and delay tumor recurrence in a transgenic model of HER2-positive breast cancer.