A survey of chromosomal instability measures across mechanistic models.

Chromosomal instability (CIN) is the persistent reshuffling of cancer karyotypes via chromosome mis-segregation during cell division. In cancer, CIN exists at varying levels that have differential effects on tumor progression. However, mis-segregation rates remain challenging to assess in human cancer despite an array of available measures. We evaluated measures of CIN by comparing quantitative methods using specific, inducible phenotypic CIN models of chromosome bridges, pseudobipolar spindles, multipolar spindles, and polar chromosomes. For each, we measured CIN fixed and timelapse fluorescence microscopy, chromosome spreads, six-centromere FISH, bulk transcriptomics, and single-cell DNA sequencing (scDNAseq). As expected, microscopy of tumor cells in live and fixed samples significantly correlated (R = 0.72; P < 0.001) and sensitively detect CIN. Cytogenetics approaches include chromosome spreads and 6-centromere FISH, which also significantly correlate (R = 0.76; P < 0.001) but had limited sensitivity for lower rates of CIN. Bulk genomic DNA signatures and bulk transcriptomic scores, CIN70 and HET70, did not detect CIN. By contrast, scDNAseq detects CIN with high sensitivity, and significantly correlates with imaging methods (R = 0.82; P < 0.001). In summary, single-cell methods such as imaging, cytogenetics, and scDNAseq can measure CIN, with the latter being the most comprehensive method accessible to clinical samples. To facilitate the comparison of CIN rates between phenotypes and methods, we propose a standardized unit of CIN: Mis-segregations per Diploid Division. This systematic analysis of common CIN measures highlights the superiority of single-cell methods and provides guidance for measuring CIN in the clinical setting.

The Right Dose: Results of a Patient Advocate-Led Survey of Individuals With Metastatic Breast Cancer Regarding Treatment-Related Side Effects and Views About Dosage Assessment to Optimize Quality of Life.

PURPOSE: Although patients with metastatic breast cancer (MBC) have been living longer with the advent of more effective treatments such as targeted therapy and immunotherapy, the disease remains incurable, and most patients will undergo therapy indefinitely. When beginning therapy, patients are typically prescribed dose often based upon the maximum tolerated dose identified in phase I clinical trials. However, patients' perspectives about tolerability and willingness to discuss individualized dosing of drugs upon initiation of a new regimen and throughout the course of treatment have not been comprehensively evaluated. METHODS: Patient advocates and medical oncologists from the Patient-Centered Dosing Initiative (PCDI) developed a survey to ascertain the prevalence and severity of MBC patients' treatment-related side effects, the level of patient-physician communication, mitigation strategies, perception about the relative efficacy of higher versus lower doses, and willingness to discuss alternative dosing. The PCDI distributed the anonymous confidential online survey in August 2020 to individuals with self-reported MBC. RESULTS: One thousand and two hundred twenty-one patients with MBC completed the survey. 86.1% (n = 1,051) reported experiencing at least one significant treatment-related side effect, and of these, 20.3% (n = 213) visited the emergency room/hospital and 43.2% (n = 454) missed at least one treatment. Nearly all patients with side effects (97.6%, n = 1,026) informed their doctor and 81.7% (n = 838) received assistance. Of the 556 patients given a dose reduction for side-effect mitigation, 82.6% (n = 459) reported relief. Notably, majority of patients (53.3%, n = 651) do not believe that higher dose is always more effective than lower dose, and 92.3% (n = 1,127) would be willing to discuss flexible dosing options with their physicians based upon personal characteristics to optimize quality of life. CONCLUSION: Given that the majority of patients with MBC experienced at least one substantial treatment-related side effect and most patients given a dose reduction reported improvement, innovative dosage-related strategies are warranted to sustain and improve patients' well-being. Patient-physician discussions in which the patient's unique attributes and circumstances are assessed upon initiation of new treatment and throughout the course of therapy may facilitate the identification of the most favorable dose for each patient, and the majority of patients would be receptive to this approach.

The reckoning of chromosomal instability: past, present, future.

Quantitative measures of CIN are crucial to our understanding of its role in cancer. Technological advances have changed the way CIN is quantified, offering increased accuracy and insight. Here, we review measures of CIN through its rise as a field, discuss considerations for its measurement, and look forward to future quantification of CIN.

Association of Neighborhood Disadvantage with Short- and Long-Term Outcomes After Pancreatectomy for Pancreatic Ductal Adenocarcinoma.

BACKGROUND: While lower socioeconomic status has been shown to correlate with worse outcomes in cancer care, data correlating neighborhood-level metrics with outcomes are scarce. We aim to explore the association between neighborhood disadvantage and both short- and long-term postoperative outcomes in patients undergoing pancreatectomy for pancreatic ductal adenocarcinoma (PDAC). PATIENTS AND METHODS: We retrospectively analyzed 243 patients who underwent resection for PDAC at a single institution between 1 January 2010 and 15 September 2021. To measure neighborhood disadvantage, the cohort was divided into tertiles by Area Deprivation Index (ADI). Short-term outcomes of interest were minor complications, major complications, unplanned readmission within 30 days, prolonged hospitalization, and delayed gastric emptying (DGE). The long-term outcome of interest was overall survival. Logistic regression was used to test short-term outcomes; Cox proportional hazards models and Kaplan-Meier method were used for long-term outcomes. RESULTS: The median ADI of the cohort was 49 (IQR 32-64.5). On adjusted analysis, the high-ADI group demonstrated greater odds of suffering a major complication (odds ratio [OR], 2.78; 95% confidence interval [CI], 1.26-6.40; p = 0.01) and of an unplanned readmission (OR, 3.09; 95% CI, 1.16-9.28; p = 0.03) compared with the low-ADI group. There were no significant differences between groups in the odds of minor complications, prolonged hospitalization, or DGE (all p > 0.05). High ADI did not confer an increased hazard of death (p = 0.63). CONCLUSIONS: We found that worse neighborhood disadvantage is associated with a higher risk of major complication and unplanned readmission after pancreatectomy for PDAC.

Diverse microtubule-targeted anticancer agents kill cells by inducing chromosome missegregation on multipolar spindles.

Microtubule-targeted agents are commonly used for cancer treatment, though many patients do not benefit. Microtubule-targeted drugs were assumed to elicit anticancer activity via mitotic arrest because they cause cell death following mitotic arrest in cell culture. However, we recently demonstrated that intratumoral paclitaxel concentrations are insufficient to induce mitotic arrest and rather induce chromosomal instability (CIN) via multipolar mitotic spindles. Here, we show in metastatic breast cancer and relevant human cellular models that this mechanism is conserved among clinically useful microtubule poisons. While multipolar divisions typically produce inviable progeny, multipolar spindles can be focused into near-normal bipolar spindles at any stage of mitosis. Using a novel method to quantify the rate of CIN, we demonstrate that cell death positively correlates with net loss of DNA. Spindle focusing decreases CIN and causes resistance to diverse microtubule poisons, which can be counteracted by addition of a drug that increases CIN without affecting spindle polarity. These results demonstrate conserved mechanisms of action and resistance for diverse microtubule-targeted agents. Trial registration: clinicaltrials.gov, NCT03393741.

A survey of CIN measures across mechanistic models.

Chromosomal instability (CIN) is the persistent reshuffling of cancer karyotypes via chromosome mis-segregation during cell division. In cancer, CIN exists at varying levels that have differential effects on tumor progression. However, mis-segregation rates remain challenging to assess in human cancer despite an array of available measures. We evaluated measures of CIN by comparing quantitative methods using specific, inducible phenotypic CIN models of chromosome bridges, pseudobipolar spindles, multipolar spindles, and polar chromosomes. For each, we measured CIN fixed and timelapse fluorescence microscopy, chromosome spreads, 6-centromere FISH, bulk transcriptomics, and single cell DNA sequencing (scDNAseq). As expected, microscopy of tumor cells in live and fixed samples correlated well (R=0.77; p<0.01) and sensitively detect CIN. Cytogenetics approaches include chromosome spreads and 6-centromere FISH, which also correlate well (R=0.77; p<0.01) but had limited sensitivity for lower rates of CIN. Bulk genomic DNA signatures and bulk transcriptomic scores, CIN70 and HET70, did not detect CIN. By contrast, single-cell DNA sequencing (scDNAseq) detects CIN with high sensitivity, and correlates very well with imaging methods (R=0.83; p<0.01). In summary, single-cell methods such as imaging, cytogenetics, and scDNAseq can measure CIN, with the latter being the most comprehensive method accessible to clinical samples. To facilitate comparison of CIN rates between phenotypes and methods, we propose a standardized unit of CIN: Mis-segregations per Diploid Division (MDD). This systematic analysis of common CIN measures highlights the superiority of single-cell methods and provides guidance for measuring CIN in the clinical setting.

Validation of Immunotherapy Response Score as Predictive of Pan-solid Tumor Anti-PD-1/PD-L1 Benefit.

Immunotherapy response score (IRS) integrates tumor mutation burden (TMB) and quantitative expression biomarkers to predict anti-PD-1/PD-L1 [PD-(L)1] monotherapy benefit. Here, we evaluated IRS in additional cohorts. Patients from an observational trial (NCT03061305) treated with anti-PD-(L)1 monotherapy were included and assigned to IRS-High (-H) versus -Low (-L) groups. Associations with real-world progression-free survival (rwPFS) and overall survival (OS) were determined by Cox proportional hazards (CPH) modeling. Those with available PD-L1 IHC treated with anti-PD-(L)1 with or without chemotherapy were separately assessed. Patients treated with PD-(L)1 and/or chemotherapy (five relevant tumor types) were assigned to three IRS groups [IRS-L divided into IRS-Ultra-Low (-UL) and Intermediate-Low (-IL), and similarly assessed]. In the 352 patient anti-PD-(L)1 monotherapy validation cohort (31 tumor types), IRS-H versus IRS-L patients had significantly longer rwPFS and OS. IRS significantly improved CPH associations with rwPFS and OS beyond microsatellite instability (MSI)/TMB alone. In a 189 patient (10 tumor types) PD-L1 IHC comparison cohort, IRS, but not PD-L1 IHC nor TMB, was significantly associated with anti-PD-L1 rwPFS. In a 1,103-patient cohort (from five relevant tumor types), rwPFS did not significantly differ in IRS-UL patients treated with chemotherapy versus chemotherapy plus anti-PD-(L)1, nor in IRS-H patients treated with anti-PD-(L)1 versus anti-PD-(L)1 + chemotherapy. IRS associations were consistent across subgroups, including both Europeans and non-Europeans. These results confirm the utility of IRS utility for predicting pan-solid tumor PD-(L)1 monotherapy benefit beyond available biomarkers and demonstrate utility for informing on anti-PD-(L)1 and/or chemotherapy treatment. Significance: This study confirms the utility of the integrative IRS biomarker for predicting anti-PD-L1/PD-1 benefit. IRS significantly improved upon currently available biomarkers, including PD-L1 IHC, TMB, and MSI status. Additional utility for informing on chemotherapy, anti-PD-L1/PD-1, and anti-PD-L1/PD-1 plus chemotherapy treatments decisions is shown.

Accuracy of models to prognosticate survival after surgery for pancreatic cancer in the era of neoadjuvant therapy.

BACKGROUND: Outcomes for pancreatic adenocarcinoma (PDAC) remain difficult to prognosticate. Multiple models attempt to predict survival following the resection of PDAC, but their utility in the neoadjuvant population is unknown. We aimed to assess their accuracy among patients that received neoadjuvant chemotherapy (NAC). METHODS: We performed a multi-institutional retrospective analysis of patients who received NAC and underwent resection of PDAC. Two prognostic systems were evaluated: the Memorial Sloan Kettering Cancer Center Pancreatic Adenocarcinoma Nomogram (MSKCCPAN) and the American Joint Committee on Cancer (AJCC) staging system. Discrimination between predicted and actual disease-specific survival was assessed using the Uno C-statistic and Kaplan-Meier method. Calibration of the MSKCCPAN was assessed using the Brier score. RESULTS: A total of 448 patients were included. There were 232 (51.8%) females, and the mean age was 64.1 years (±9.5). Most had AJCC Stage I or II disease (77.7%). For the MSKCCPAN, the Uno C-statistic at 12-, 24-, and 36-month time points was 0.62, 0.63, and 0.62, respectively. The AJCC system demonstrated similarly mediocre discrimination. The Brier score for the MSKCCPAN was 0.15 at 12 months, 0.26 at 24 months, and 0.30 at 36 months, demonstrating modest calibration. CONCLUSIONS: Current survival prediction models and staging systems for patients with PDAC undergoing resection after NAC have limited accuracy.

Misaligned Chromosomes are a Major Source of Chromosomal Instability in Breast Cancer.

Chromosomal instability (CIN), the persistent reshuffling of chromosomes during mitosis, is a hallmark of human cancers that contributes to tumor heterogeneity and has been implicated in driving metastasis and altering responses to therapy. Though multiple mechanisms can produce CIN, lagging chromosomes generated from abnormal merotelic attachments are the major cause of CIN in a variety of cell lines, and are expected to predominate in cancer. Here, we quantify CIN in breast cancer using a tumor microarray, matched primary and metastatic samples, and patient-derived organoids from primary breast cancer. Surprisingly, misaligned chromosomes are more common than lagging chromosomes and represent a major source of CIN in primary and metastatic tumors. This feature of breast cancers is conserved in a majority of breast cancer cell lines. Importantly, though a portion of misaligned chromosomes align before anaphase onset, the fraction that remain represents the largest source of CIN in these cells. Metastatic breast cancers exhibit higher rates of CIN than matched primary cancers, primarily due to increases in misaligned chromosomes. Whether CIN causes immune activation or evasion is controversial. We find that misaligned chromosomes result in immune-activating micronuclei substantially less frequently than lagging and bridge chromosomes and that breast cancers with greater frequencies of lagging chromosomes and chromosome bridges recruit more stromal tumor-infiltrating lymphocytes. These data indicate misaligned chromosomes represent a major mechanism of CIN in breast cancer and provide support for differential immunostimulatory effects of specific types of CIN. Significance: We surveyed the single-cell landscape of mitotic defects that generate CIN in primary and metastatic breast cancer and relevant models. Misaligned chromosomes predominate, and are less immunostimulatory than other chromosome segregation errors.

Development and validation of an integrative pan-solid tumor predictor of PD-1/PD-L1 blockade benefit.

BACKGROUND: Anti-PD-1 and PD-L1 (collectively PD-[L]1) therapies are approved for many advanced solid tumors. Biomarkers beyond PD-L1 immunohistochemistry, microsatellite instability, and tumor mutation burden (TMB) may improve benefit prediction. METHODS: Using treatment data and genomic and transcriptomic tumor tissue profiling from an observational trial (NCT03061305), we developed Immunotherapy Response Score (IRS), a pan-tumor predictive model of PD-(L)1 benefit. IRS real-world progression free survival (rwPFS) and overall survival (OS) prediction was validated in an independent cohort of trial patients. RESULTS: Here, by Cox modeling, we develop IRS-which combines TMB with CD274, PDCD1, ADAM12 and TOP2A quantitative expression-to predict pembrolizumab rwPFS (648 patients; 26 tumor types; IRS-High or -Low groups). In the 248 patient validation cohort (248 patients; 24 tumor types; non-pembrolizumab PD-[L]1 monotherapy treatment), median rwPFS and OS are significantly longer in IRS-High vs. IRS-Low patients (rwPFS adjusted hazard ratio [aHR] 0.52, p = 0.003; OS aHR 0.49, p = 0.005); TMB alone does not significantly predict PD-(L)1 rwPFS nor OS. In 146 patients treated with systemic therapy prior to pembrolizumab monotherapy, pembrolizumab rwPFS is only significantly longer than immediately preceding therapy rwPFS in IRS-High patients (interaction test p = 0.001). In propensity matched lung cancer patients treated with first-line pembrolizumab monotherapy or pembrolizumab+chemotherapy, monotherapy rwPFS is significantly shorter in IRS-Low patients, but is not significantly different in IRS-High patients. Across 24,463 molecularly-evaluable trial patients, 7.6% of patients outside of monotherapy PD-(L)1 approved tumor types are IRS-High/TMB-Low. CONCLUSIONS: The validated, predictive, pan-tumor IRS model can expand PD-(L)1 monotherapy benefit outside currently approved indications.

Therapies activating the immune system (checkpoint inhibitors) have revolutionized the treatment of patients with advanced cancer, however new molecular tests may better identify patients who could benefit. Using treatment data and clinical molecular test results, we report the development and validation of Immunotherapy Response Score (IRS) to predict checkpoint inhibitor benefit. Across patients with more than 20 advanced cancer types, IRS better predicted checkpoint inhibitor benefit than currently available tests. Data from >20,000 patients showed that IRS identifies ~8% of patients with advanced cancer who may dramatically benefit from checkpoint inhibitors but would not receive them today based on currently available tests. Our approach may help clinicians to decide which patients should receive checkpoint inhibitors to treat their disease.

Clinical utility of a regional precision medicine molecular tumor board and challenges to implementation.

PURPOSE: Molecular tumor boards provide precision treatment recommendations based on cancer genomic profile. However, practical barriers limit their benefits. We studied the clinical utility of the precision medicine molecular tumor board (PMMTB) and described challenges with PMMTB implementation. METHODS: An observational cohort study included patients reviewed by the PMMTB between September 2015 to December 2017. Patients who had consented to the registry study were included. The primary endpoint of this study was time on treatment (ToT) ratio. Clinical utility was established if the primary endpoint had least 15% of patients achieving a ToT ratio of ≥1.3. RESULTS: Overall, 278 patients were presented to the PMMTB and 113 cases were included in the final analysis. The PMMTB identified at least one nonstandard of care (SOC) clinically actionable mutation for 69.0% (78/113) of cases. In patients who received non-SOC treatment, 43.8% (7/16) achieved a ToT ratio of 1.3 or more (p < 0.001). Fifty-nine patients did not receive non-SOC recommendations. Reasons for not pursuing treatment included 35.6% having response to current treatment, 20.3% died prior to starting or considering PMMTB recommendations, 13.6% pursued other treatment options based on clinician discretion, another 10.2% pursued other treatment options because clinical trials recommended were not geographically accessible, 8.5% had rapid decline of performance status, 6.8% lacked of financial support for treatment, and 5.1% were excluded from clinical trials due to abnormal laboratory values. CONCLUSION: The regional PMMTB non-SOC recommendations benefitted a majority of patients and additional processes were implemented to assist with non-SOC treatment accessibility.

Patient-centered dosing: oncologists' perspectives about treatment-related side effects and individualized dosing for patients with metastatic breast cancer (MBC).

PURPOSE: Although metastatic breast cancer (MBC) is treatable, it is not curable and most patients remain on treatment indefinitely. While oncologists commonly prescribe the recommended starting dose (RSD) from the FDA-approved label, patient tolerance may differ from that seen in clinical trials. We report on a survey of medical oncologists' perspectives about treatment-related toxicity and willingness to discuss flexible dosing with patients. METHODS: We disseminated a confidential survey via social media/email in Spring 2021. Eligible respondents needed to be US-based medical oncologists with experience treating patients with MBC. RESULTS: Of 131 responses, 119 were eligible. Physicians estimated that 47% of their patients reported distressing treatment-related side effects; of these, 15% visited the Emergency Room/hospital and 37% missed treatment. 74% (n = 87) of doctors reported improvement of patient symptoms after dose reduction. 87% (n = 104) indicated that they had ever, if appropriate, initiated treatment at lower doses. Most (85%, n = 101) respondents did not believe that the RSD is always more effective than a lower dose and 97% (n = 115) were willing to discuss individualized dosing with patients. CONCLUSION: Treatment-related side effects are prevalent among patients with MBC, resulting in missed treatments and acute care visits. To help patients tolerate treatment, oncologists may decrease initial and/or subsequent doses. The majority of oncologists reject the premise that a higher dose is always superior and are willing to discuss individualized dosing with patients. Given potential improvements regarding quality of life and clinical care, dose modifications should be part of routine shared decision-making between patients and oncologists.

Increased Aurora B expression reduces substrate phosphorylation and induces chromosomal instability.

Increased Aurora B protein expression, which is common in cancers, is expected to increase Aurora B kinase activity, yielding elevated phosphorylation of Aurora B substrates. In contrast, here we show that elevated expression of Aurora B reduces phosphorylation of six different Aurora B substrates across three species and causes defects consistent with Aurora B inhibition. Complexes of Aurora B and its binding partner INCENP autophosphorylate in trans to achieve full Aurora B activation. Increased expression of Aurora B mislocalizes INCENP, reducing the local concentration of Aurora B:INCENP complexes at the inner centromere/kinetochore. Co-expression of INCENP rescues Aurora B kinase activity and mitotic defects caused by elevated Aurora B. However, INCENP expression is not elevated in concert with Aurora B in breast cancer, and increased expression of Aurora B causes resistance rather than hypersensitivity to Aurora B inhibitors. Thus, increased Aurora B expression reduces, rather than increases, Aurora B kinase activity.

Quantifying chromosomal instability from intratumoral karyotype diversity using agent-based modeling and Bayesian inference.

Chromosomal instability (CIN)-persistent chromosome gain or loss through abnormal mitotic segregation-is a hallmark of cancer that drives aneuploidy. Intrinsic chromosome mis-segregation rate, a measure of CIN, can inform prognosis and is a promising biomarker for response to anti-microtubule agents. However, existing methodologies to measure this rate are labor intensive, indirect, and confounded by selection against aneuploid cells, which reduces observable diversity. We developed a framework to measure CIN, accounting for karyotype selection, using simulations with various levels of CIN and models of selection. To identify the model parameters that best fit karyotype data from single-cell sequencing, we used approximate Bayesian computation to infer mis-segregation rates and karyotype selection. Experimental validation confirmed the extensive chromosome mis-segregation rates caused by the chemotherapy paclitaxel (18.5 ± 0.5/division). Extending this approach to clinical samples revealed that inferred rates fell within direct observations of cancer cell lines. This work provides the necessary framework to quantify CIN in human tumors and develop it as a predictive biomarker.

DNA contains all the information that cells need to function. The DNA inside cells is housed in structures called chromosomes, and most healthy human cells contain 23 pairs. When a cell divides, all chromosomes are copied so that each new cell gets a complete set. However, sometimes the process of separating chromosomes is faulty, and new cells may get incorrect numbers of chromosomes during cell division. Cancer cells frequently exhibit this behavior, which is called chromosomal instability', or CIN. Chromosomal instability affects many cancer cells with varying severity. In cancers with high chromosomal instability, the number of chromosomes may change almost every time the cells divide. These cancers are often the most aggressive and difficult to treat. Scientists can estimate chromosomal instability by counting differences in the number of chromosomes across many cells. However, many cells that are missing chromosomes die, resulting in inaccurate measures of chromosomal instability. To find a solution to this problem, Lynch et al. counted chromosomes in human cells with different levels of chromosomal instability and created a computer model to work out the relationship between chromosomal instability and chromosome number. The model could account for both living and dead cells, which gave more accurate results. Lynch et al. then confirmed the accuracy of their approach by using it on a group of cells treated with a chemotherapy drug that causes a known level of chromosomal instability. They also used existing data from breast and bowel cancer, which revealed that levels of chromosomal instability varied between one mistake per three to twenty cell divisions. Lower levels of chromosomal instability can be linked to a better prognosis for cancer patients, but it currently cannot be measured reliably. These results may help to reveal the causes of chromosomal instability and the role it has in cancer. If this method is successfully applied to patient samples, it could also improve our ability to predict how each cancer will progress and may lead to better treatments.

Classes of therapeutics to amplify the immune response.

PURPOSE: Conventional chemotherapies are a mainstay for metastatic breast cancers, though durable response is rare. Immunotherapies promise long-term responses thorough immune activation but have been underwhelming in breast cancer relative to other cancer types. Here, we review the mechanisms of existing strategies including chemotherapies and how they may cause breast cancers to become immunogenic to identify potential biomarkers for combinations of conventional and immunotherapies. CONCLUSION: Mechanistic considerations should inform biomarker development and patient selection for therapeutic combinations of drugs to combine with immune-checkpoint inhibitors.

Breast cancer immunotherapy: current biomarkers and the potential of in vitro assays.

Breakthroughs in metastatic breast cancer care require new model systems that can identify the unique features and vulnerabilities of each cancer. Primary tumor cultures are proposed to efficiently screen multiple treatment options in a patient-specific strategy to maximize therapeutic benefit, minimize toxicity, and enable mechanistic insights that inspire future biomarkers for patient selection. To realize the potential of patient-specific cultures, new tools are needed to capture cell-by-cell variability in behavior and dynamic response to treatments in living 3D specimens. Potential bioengineering tools that can achieve this include optical microscopy to image single-cell dynamics and microphysiological in vitro systems to evaluate cell-cell interactions and immunotherapies.

Chromosomal instability sensitizes patient breast tumors to multipolar divisions induced by paclitaxel.

Paclitaxel (Taxol) is a cornerstone of cancer treatment. However, its mechanism of cytotoxicity is incompletely understood and not all patients benefit from treatment. We show that patients with breast cancer did not accumulate sufficient intratumoral paclitaxel to induce mitotic arrest in tumor cells. Instead, clinically relevant concentrations induced multipolar mitotic spindle formation. However, the extent of early multipolarity did not predict patient response. Whereas multipolar divisions frequently led to cell death, multipolar spindles focused into bipolar spindles before division at variable frequency, and maintaining multipolarity throughout mitosis was critical to induce the high rates of chromosomal instability necessary for paclitaxel to elicit cell death. Increasing multipolar divisions in paclitaxel resulted in improved cytotoxicity. Conversely, decreasing paclitaxel-induced multipolar divisions reduced paclitaxel efficacy. Moreover, we found that preexisting chromosomal instability sensitized breast cancer cells to paclitaxel. Both genetic and pharmacological methods of inducing chromosomal instability were sufficient to increase paclitaxel efficacy. In patients, the amount of pretreatment chromosomal instability directly correlated with taxane response in metastatic breast cancer such that patients with a higher rate of preexisting chromosomal instability showed improved response to taxanes. Together, these results support the use of baseline rates of chromosomal instability as a predictive biomarker for paclitaxel response. Furthermore, they suggest that agents that increase chromosomal instability or maintain multipolar spindles throughout mitosis will improve the clinical utility of paclitaxel.

Paclitaxel Induces Micronucleation and Activates Pro-Inflammatory cGAS-STING Signaling in Triple-Negative Breast Cancer.

Taxanes remain one of the most effective medical treatments for breast cancer. Clinical trials have coupled taxanes with immune checkpoint inhibitors in patients with triple-negative breast cancer (TNBC) with promising results. However, the mechanism linking taxanes to immune activation is unclear. To determine if paclitaxel could elicit an antitumoral immune response, we sampled tumor tissues from patients with TNBC receiving weekly paclitaxel (80 mg/m2) and found increased stromal tumor-infiltrating lymphocytes and micronucleation over baseline in three of six samples. At clinically relevant concentrations, paclitaxel can induce chromosome missegregation on multipolar spindles during mitosis. Consequently, post-mitotic cells are multinucleated and contain micronuclei, which often activate cyclic GMP-AMP synthase (cGAS) and may induce a type I IFN response reliant on the stimulator of IFN genes (STING) pathway. Other microtubule-targeting agents, eribulin and vinorelbine, recapitulate this cGAS/STING response and increased the expression of immune checkpoint molecule, PD-L1, in TNBC cell lines. To test the possibility that microtubule-targeting agents sensitize tumors that express cGAS to immune checkpoint inhibitors, we identified 10 patients with TNBC treated with PD-L1 or PD-1, seven of whom also received microtubule-targeting agents. Elevated baseline cGAS expression significantly correlated with treatment response in patients receiving microtubule-targeting agents in combination with immune checkpoint inhibitors. Our study identifies a mechanism by which microtubule-targeting agents can potentiate an immune response in TNBC. Further, baseline cGAS expression may predict patient treatment response to therapies combining microtubule-targeting agents and immune checkpoint inhibitors.

Real-World Performance of a Comprehensive Genomic Profiling Test Optimized for Small Tumor Samples.

PURPOSE: Tissue-based comprehensive genomic profiling (CGP) is increasingly used for treatment selection in patients with advanced cancer; however, tissue availability may limit widespread implementation. Here, we established real-world CGP tissue availability and assessed CGP performance on consecutively received samples. MATERIALS AND METHODS: We conducted a post hoc, nonprespecified analysis of 32,048 consecutive tumor tissue samples received for StrataNGS, a multiplex polymerase chain reaction (PCR)-based comprehensive genomic profiling (PCR-CGP) test, as part of an ongoing observational trial (NCT03061305). Sample characteristics and PCR-CGP performance were assessed across all tested samples, including exception samples not meeting minimum input quality control (QC) requirements (< 20% tumor content [TC], < 2 mm2 tumor surface area [TSA], DNA or RNA yield < 1 ng/µL, or specimen age > 5 years). Tests reporting ≥ 1 prioritized alteration or meeting TC and sequencing QC were considered successful. For prostate carcinoma and lung adenocarcinoma, tests reporting ≥ 1 actionable or informative alteration or meeting TC and sequencing QC were considered actionable. RESULTS: Among 31,165 (97.2%) samples where PCR-CGP was attempted, 10.7% had < 20% TC and 59.2% were small (< 25 mm2 tumor surface area). Of 31,101 samples evaluable for input requirements, 8,089 (26.0%) were exceptions not meeting requirements. However, 94.2% of the 31,101 tested samples were successfully reported, including 80.5% of exception samples. Positive predictive value of PCR-CGP for ERBB2 amplification in exceptions and/or sequencing QC-failure breast cancer samples was 96.7%. Importantly, 84.0% of tested prostate carcinomas and 87.9% of lung adenocarcinomas yielded results informing treatment selection. CONCLUSION: Most real-world tissue samples from patients with advanced cancer desiring CGP are limited, requiring optimized CGP approaches to produce meaningful results. An optimized PCR-CGP test, coupled with an inclusive exception testing policy, delivered reportable results for > 94% of samples, potentially expanding the proportion of CGP-testable patients and impact of biomarker-guided therapies.