Tumor microenvironment immunomodulation by nanoformulated TLR 7/8 agonist and PI3k delta inhibitor enhances therapeutic benefits of radiotherapy.

Infiltration of immunosuppressive cells into the breast tumor microenvironment (TME) is associated with suppressed effector T cell (Teff) responses, accelerated tumor growth, and poor clinical outcomes. Previous studies from our group and others identified infiltration of immunosuppressive myeloid-derived suppressor cells (MDSCs) and regulatory T cells (Tregs) as critical contributors to immune dysfunction in the orthotopic claudin-low tumor model, limiting the efficacy of adoptive cellular therapy. However, approaches to target these cells in the TME are currently lacking. To overcome this barrier, polymeric micellular nanoparticles (PMNPs) were used for the co-delivery of small molecule drugs activating Toll-like receptors 7 and 8 (TLR7/8) and inhibiting PI3K delta (PI3Kδ). The immunomodulation of the TME by TLR7/8 agonist and PI3K inhibitor led to type 1 macrophage polarization, decreased MDSC accumulation and selectively decreased tissue-resident Tregs in the TME, while enhancing the T and B cell adaptive immune responses. PMNPs significantly enhanced the anti-tumor activity of local radiation therapy (RT) in mice bearing orthotopic claudin-low tumors compared to RT alone. Taken together, these data demonstrate that RT combined with a nanoformulated immunostimulant diminished the immunosuppressive TME resulting in tumor regression. These findings set the stage for clinical studies of this approach.

Quantitative proteomic mass spectrometry of protein kinases to determine dynamic heterogeneity of the human kinome.

The kinome is a dynamic system of kinases regulating signaling networks in cells and dysfunction of protein kinases contributes to many diseases. Regulation of the protein expression of kinases alters cellular responses to environmental changes and perturbations. We configured a library of 672 proteotypic peptides to quantify >300 kinases in a single LC-MS experiment using ten micrograms protein from human tissues including biopsies. This enables absolute quantitation of kinase protein abundance at attomole-femtomole expression levels, requiring no kinase enrichment and less than ten micrograms of starting protein from flash-frozen and formalin fixed paraffin embedded tissues. Breast cancer biopsies, organoids, and cell lines were analyzed using the SureQuant method, demonstrating the heterogeneity of kinase protein expression across and within breast cancer clinical subtypes. Kinome quantitation was coupled with nanoscale phosphoproteomics, providing a feasible method for novel clinical diagnosis and understanding of patient kinome responses to treatment.

Single-cell transcriptional atlas of human breast cancers and model systems.

BACKGROUND: Breast cancer's complex transcriptional landscape requires an improved understanding of cellular diversity to identify effective treatments. The study of genetic variations among breast cancer subtypes at single-cell resolution has potential to deepen our insights into cancer progression. METHODS: In this study, we amalgamate single-cell RNA sequencing data from patient tumours and matched lymph metastasis, reduction mammoplasties, breast cancer patient-derived xenografts (PDXs), PDX-derived organoids (PDXOs), and cell lines resulting in a diverse dataset of 117 samples with 506 719 total cells. These samples encompass hormone receptor positive (HR+), human epidermal growth factor receptor 2 positive (HER2+), and triple-negative breast cancer (TNBC) subtypes, including isogenic model pairs. Herein, we delineated similarities and distinctions across models and patient samples and explore therapeutic drug efficacy based on subtype proportions. RESULTS: PDX models more closely resemble patient samples in terms of tumour heterogeneity and cell cycle characteristics when compared with TNBC cell lines. Acquired drug resistance was associated with an increase in basal-like cell proportions within TNBC PDX tumours as defined with SCSubtype and TNBCtype cell typing predictors. All patient samples contained a mixture of subtypes; compared to primary tumours HR+ lymph node metastases had lower proportions of HER2-Enriched cells. PDXOs exhibited differences in metabolic-related transcripts compared to PDX tumours. Correlative analyses of cytotoxic drugs on PDX cells identified therapeutic efficacy was based on subtype proportion. CONCLUSIONS: We present a substantial multimodel dataset, a dynamic approach to cell-wise sample annotation, and a comprehensive interrogation of models within systems of human breast cancer. This analysis and reference will facilitate informed decision-making in preclinical research and therapeutic development through its elucidation of model limitations, subtype-specific insights and novel targetable pathways. KEY POINTS: Patient-derived xenografts models more closely resemble patient samples in tumour heterogeneity and cell cycle characteristics when compared with cell lines. 3D organoid models exhibit differences in metabolic profiles compared to their in vivo counterparts. A valuable multimodel reference dataset that can be useful in elucidating model differences and novel targetable pathways.

Estrogen signaling suppresses tumor-associated tissue eosinophilia to promote breast tumor growth.

Estrogens regulate eosinophilia in asthma and other inflammatory diseases. Further, peripheral eosinophilia and tumor-associated tissue eosinophilia (TATE) predicts a better response to immune checkpoint blockade (ICB) in breast cancer. However, how and if estrogens affect eosinophil biology in tumors and how this influences ICB efficacy has not been determined. Here, we report that estrogens decrease the number of peripheral eosinophils and TATE, and this contributes to increased tumor growth in validated murine models of breast cancer and melanoma. Moreover, estrogen signaling in healthy female mice also suppressed peripheral eosinophil prevalence by decreasing the proliferation and survival of maturing eosinophils. Inhibiting estrogen receptor (ER) signaling decreased tumor growth in an eosinophil-dependent manner. Further, the efficacy of ICBs was increased when administered in combination with anti-estrogens. These findings highlight the importance of ER signaling as a regulator of eosinophil biology and TATE and highlight the potential near-term clinical application of ER modulators to increase ICB efficacy in multiple tumor types.

Stain SAN: simultaneous augmentation and normalization for histopathology images.

Purpose: We address the need for effective stain domain adaptation methods in histopathology to enhance the performance of downstream computational tasks, particularly classification. Existing methods exhibit varying strengths and weaknesses, prompting the exploration of a different approach. The focus is on improving stain color consistency, expanding the stain domain scope, and minimizing the domain gap between image batches. Approach: We introduce a new domain adaptation method, Stain simultaneous augmentation and normalization (SAN), designed to adjust the distribution of stain colors to align with a target distribution. Stain SAN combines the merits of established methods, such as stain normalization, stain augmentation, and stain mix-up, while mitigating their inherent limitations. Stain SAN adapts stain domains by resampling stain color matrices from a well-structured target distribution. Results: Experimental evaluations of cross-dataset clinical estrogen receptor status classification demonstrate the efficacy of Stain SAN and its superior performance compared with existing stain adaptation methods. In one case, the area under the curve (AUC) increased by 11.4%. Overall, our results clearly show the improvements made over the history of the development of these methods culminating with substantial enhancement provided by Stain SAN. Furthermore, we show that Stain SAN achieves results comparable with the state-of-the-art generative adversarial network-based approach without requiring separate training for stain adaptation or access to the target domain during training. Stain SAN's performance is on par with HistAuGAN, proving its effectiveness and computational efficiency. Conclusions: Stain SAN emerges as a promising solution, addressing the potential shortcomings of contemporary stain adaptation methods. Its effectiveness is underscored by notable improvements in the context of clinical estrogen receptor status classification, where it achieves the best AUC performance. The findings endorse Stain SAN as a robust approach for stain domain adaptation in histopathology images, with implications for advancing computational tasks in the field.

Association between tumor-infiltrating lymphocytes and survival in patients with metastatic breast cancer receiving first-line chemotherapy: analysis of CALGB 40502.

Association of stromal tumor-infiltrating lymphocytes (sTILs) with survival outcomes among patients with metastatic breast cancer (MBC) remains unclear. The primary objective was to evaluate the association of sTILs with progression-free survival in randomized phase III trial CALGB 40502. sTILs were associated with progression-free and overall survival in chemotherapy-treated MBC when controlling for treatment arm; however, this effect did not remain significant after additional adjustment for hormone receptor status. CALGB is now part of the Alliance for Clinical Trials in Oncology. Trial Registration: ClinicalTrials.gov: NCT00785291.

Development and Characterization of Syngeneic Orthotopic Transplant Models of Obesity-Responsive Triple-Negative Breast Cancer in C57BL/6J Mice.

Obesity is an established risk and progression factor for triple-negative breast cancer (TNBC), but preclinical studies to delineate the mechanisms underlying the obesity-TNBC link as well as strategies to break that link are constrained by the lack of tumor models syngeneic to obesity-prone mouse strains. C3(1)/SV40 T-antigen (C3-TAg) transgenic mice on an FVB genetic background develop tumors with molecular and pathologic features that closely resemble human TNBC, but FVB mice are resistant to diet-induced obesity (DIO). Herein, we sought to develop transplantable C3-TAg cell lines syngeneic to C57BL/6 mice, an inbred mouse strain that is sensitive to DIO. We backcrossed FVB-Tg(C3-1-TAg)cJeg/JegJ to C57BL/6 mice for ten generations, and spontaneous tumors from those mice were excised and used to generate four clonal cell lines (B6TAg1.02, B6TAg2.03, B6TAg2.10, and B6TAg2.51). We characterized the growth of the four cell lines in both lean and DIO C57BL/6J female mice and performed transcriptomic profiling. Each cell line was readily tumorigenic and had transcriptional profiles that clustered as claudin-low, yet markedly differed from each other in their rate of tumor progression and transcriptomic signatures for key metabolic, immune, and oncogenic signaling pathways. DIO accelerated tumor growth of orthotopically transplanted B6TAg1.02, B6TAg2.03, and B6TAg2.51 cells. Thus, the B6TAg cell lines described herein offer promising and diverse new models to augment the study of DIO-associated TNBC.

A Phase I Trial of Alpelisib Combined With Capecitabine in Patients With HER2-Negative Metastatic Breast Cancer.

BACKGROUND: Alpelisib is an oral α-specific class I PI3K inhibitor approved in combination with fulvestrant for the treatment of PIK3CA-mutated hormone receptor-positive (HR+), human epidermal growth factor receptor 2 negative (HER2-) metastatic breast cancer. The tolerability of this drug with the oral chemotherapy capecitabine is unknown. PATIENTS AND METHODS: This phase I trial evaluated the dose-limiting toxicities (DLTs) and maximum tolerated dose (MTD) of alpelisib (250 mg or 300 mg daily for 3-weeks) with capecitabine (1000 mg/m2 twice daily for 2-weeks followed by a 1-week rest period) in patients with metastatic HER2-negative breast cancer, regardless of PIK3CA mutation status. RESULTS: Eighteen patients were treated with alpelisib-capecitabine. Half of the patients had HR+ breast cancer, and 16 had prior systemic therapy for metastatic disease. The MTD of alpelisib was 250 mg daily in combination with capecitabine 1000 mg/m2 twice daily. DLTs included hyperglycemia, QTc prolongation, fatigue, and chest pain. The most common grade 3 adverse event (AE) was hyperglycemia (28%). No grade 4 AEs were observed. Three patients discontinued therapy due to an AE. One-third of patients required dose reduction of both alpelisib and capecitabine. Four patients experienced a partial response and 8 patients experienced stable disease. The median progression-free survival was 9.7 months (95% CI 2.8-13.5 months) and median overall survival was 18.2 months (95% CI 7.2-35.2 months). Twelve patients had PIK3CA mutation testing completed, of these 2 had known or likely deleterious PIK3CA mutation. CONCLUSION: This study provides safety data for an oral combination therapy of alpelisib-capecitabine and defines tolerable doses for further study.

Comparative biological activity of palbociclib and ribociclib in hormone receptor-positive breast cancer.

This study examines the biological effects of palbociclib and ribociclib in hormone receptor-positive breast cancer, pivotal to the HARMONIA prospective phase III clinical trial. We explore the downstream impacts of these CDK4/6 inhibitors, focusing on cell lines and patient-derived tumor samples. We treated HR+ breast cancer cell lines (T47D, MCF7, and BT474) with palbociclib or ribociclib (100 nM or 500 nM), alone or combined with fulvestrant (1 nM), over periods of 24, 72, or 144 h. Our assessments included PAM50 gene expression, RB1 phosphorylation, Lamin-B1 protein levels, and senescence-associated ß-galactosidase activity. We further analyzed PAM50 gene signatures from the CORALLEEN and NeoPalAna phase II trials. Both CDK4/6 inhibitors similarly inhibited proliferation across the cell lines. At 100 nM, both drugs partially reduced p-RB1, with further decreases at 500 nM over 144 h. Treatment led to reduced Lamin-B1 expression and increased senescence-associated ß-galactosidase activity. Both drugs enhanced Luminal A and reduced Luminal B and proliferation signatures at both doses. However, the HER2-enriched signature significantly diminished only at the higher dose of 500 nM. Corresponding changes were observed in tumor samples from the CORALLEEN and NeoPalAna studies. At 2 weeks of treatment, both drugs significantly reduced the HER2-enriched signature, but at surgery, this reduction was consistent only with ribociclib. Our findings suggest that while both CDK4/6 inhibitors effectively modulate key biological pathways in HR+/HER2- breast cancer, nuances in their impact, particularly on the HER2-enriched signature, are dose-dependent, influenced by the addition of fulvestrant and warrant further investigation.

HER2DX Genomic Assay in HER2-Positive Early Breast Cancer Treated with Trastuzumab and Pertuzumab: A Correlative Analysis from the PHERGain Phase II Trial.

PURPOSE: The purpose of this study was to assess the predictive capability of HER2DX assay following (neo)adjuvant trastuzumab-pertuzumab (HP)-based therapy in HER2-positive (HER2+) early breast cancer. EXPERIMENTAL DESIGN: HER2DX was analyzed in baseline pretreatment tumors from the PHERGain trial. Patients with stage I-IIIA HER2+ early breast cancer were randomized to group A [docetaxel, carboplatin, and HP (TCHP)] and group B (HP ± endocrine therapy). PET response was evaluated after two cycles. Group A received TCHP for six cycles regardless of PET response. Group B continued with HP ± endocrine therapy for six cycles (PET responders) or with TCHP for six cycles (PET nonresponders). The primary objective of this retrospective study was to associate the HER2DX pathologic complete response (pCR) score with pCR. The secondary objective was the association of the HER2DX risk score with 3-year invasive disease-free survival (iDFS). RESULTS: HER2DX was performed on 292 (82.0%) tumors. The overall pCR rate was 38.0%, with pCR rates of 56.4% in group A and 33.8% in group B. In multivariable analysis including treatment and clinicopathologic factors, the HER2DX pCR score (continuous variable) significantly correlated with pCR [OR, 1.29; 95% confidence interval (CI), 1.10-1.54; P < 0.001]. HER2DX-defined pCR-high, -med, and -low groups exhibited pCR rates of 50.4%, 35.8%, and 23.2%, respectively (pCR-high vs. pCR-low OR, 3.27; 95% CI, 1.54-7.09; P < 0.001). In patients with residual disease, the HER2DX high-risk group demonstrated numerically worse 3-year iDFS than the low-risk group (89.8% vs. 100%; HR, 2.70; 95% CI, 0.60-12.18; P = 0.197). CONCLUSIONS: HER2DX predicts pCR in the context of neoadjuvant HP-based therapy, regardless of chemotherapy addition, and might identify patients at higher risk of recurrence among patients with residual disease.

Visual Intratumor Heterogeneity and Breast Tumor Progression.

High intratumoral heterogeneity is thought to be a poor prognostic indicator. However, the source of heterogeneity may also be important, as genomic heterogeneity is not always reflected in histologic or 'visual' heterogeneity. We aimed to develop a predictor of histologic heterogeneity and evaluate its association with outcomes and molecular heterogeneity. We used VGG16 to train an image classifier to identify unique, patient-specific visual features in 1655 breast tumors (5907 core images) from the Carolina Breast Cancer Study (CBCS). Extracted features for images, as well as the epithelial and stromal image components, were hierarchically clustered, and visual heterogeneity was defined as a greater distance between images from the same patient. We assessed the association between visual heterogeneity, clinical features, and DNA-based molecular heterogeneity using generalized linear models, and we used Cox models to estimate the association between visual heterogeneity and tumor recurrence. Basal-like and ER-negative tumors were more likely to have low visual heterogeneity, as were the tumors from younger and Black women. Less heterogeneous tumors had a higher risk of recurrence (hazard ratio = 1.62, 95% confidence interval = 1.22-2.16), and were more likely to come from patients whose tumors were comprised of only one subclone or had a TP53 mutation. Associations were similar regardless of whether the image was based on stroma, epithelium, or both. Histologic heterogeneity adds complementary information to commonly used molecular indicators, with low heterogeneity predicting worse outcomes. Future work integrating multiple sources of heterogeneity may provide a more comprehensive understanding of tumor progression.

Associations of Immune Checkpoint Predictive Biomarkers (MHC-I and MHC-II) with Clinical and Molecular Features in a Diverse Breast Cancer Cohort.

PURPOSE: Immunotherapy (IO) in triple-negative breast cancer (TNBC) has improved survival outcomes, with promising improvements in pCR rates among early high-risk hormone receptor (HR)+/HER2- breast cancers. However, biomarkers are needed to select patients likely to benefit from IO. MHC-I and tumor-specific MHC-II (tsMHC-II) expression are candidate biomarkers for PD-(L)1 checkpoint inhibition but existing data from clinical trials included limited racial/ethnic diversity. EXPERIMENTAL DESIGN: We performed multiplexed immunofluorescence assays in the Carolina Breast Cancer Study (CBCS; n = 1,628, 48% Black, 52% non-Black). Intrinsic subtype and P53 mutant-like status were identified using RNA-based multigene assays. We ranked participants based on tumoral MHC-I intensity (top 33% categorized as "MHC-Ihigh") and MHC-II+ (≥5% of tumor cells as tsMHC-II+). MHC-I/II were evaluated in association with clinicopathological features by race. RESULTS: Black participants had higher frequency of TNBC (25% vs. 12.5%, P ≤ 0.001) and basal-like (30% vs. 14%, P ≤ 0.001) tumors overall, and higher frequency of basal-like (11% vs. 5.5%, P = 0.002) and TP53 mutant tumors (26% vs. 17%, P = 0.002) among HR+/HER2-. The frequency of tsMHC-II+ was higher in HR+/HER2- Black participants (7.9% vs. 4.9%, P = 0.04). Black participants also had higher frequency of MHC-Ihigh (38.7% vs. 28.2%, P < 0.001), which was significant among HR+/HER2- (28.2% vs. 22.1%, P = 0.02). CONCLUSIONS: In this diverse study population, MHC-I and MHC-II tumor cell expression were more highly expressed in HR+/HER2- tumors from Black women, underscoring the importance of diverse and equitable enrollment in future IO trials.

Defining the Regulatory Logic of Breast Cancer Using Single-Cell Epigenetic and Transcriptome Profiling.

Annotation of the cis-regulatory elements that drive transcriptional dysregulation in cancer cells is critical to improving our understanding of tumor biology. Herein, we present a compendium of matched chromatin accessibility (scATAC-seq) and transcriptome (scRNA-seq) profiles at single-cell resolution from human breast tumors and healthy mammary tissues processed immediately following surgical resection. We identify the most likely cell-of-origin for luminal breast tumors and basal breast tumors and then introduce a novel methodology that implements linear mixed-effects models to systematically quantify associations between regions of chromatin accessibility (i.e. regulatory elements) and gene expression in malignant cells versus normal mammary epithelial cells. These data unveil regulatory elements with that switch from silencers of gene expression in normal cells to enhancers of gene expression in cancer cells, leading to the upregulation of clinically relevant oncogenes. To translate the utility of this dataset into tractable models, we generated matched scATAC-seq and scRNA-seq profiles for breast cancer cell lines, revealing, for each subtype, a conserved oncogenic gene expression program between in vitro and in vivo cells. Together, this work highlights the importance of non-coding regulatory mechanisms that underlie oncogenic processes and the ability of single-cell multi-omics to define the regulatory logic of BC cells at single-cell resolution.

OptimICE-RD: sacituzumab govitecan + pembrolizumab vs pembrolizumab (± capecitabine) for residual triple-negative breast cancer.

Patients with early-stage triple-negative breast cancer (TNBC) with residual invasive disease after neoadjuvant therapy have a high risk of recurrence even with neoadjuvant and adjuvant treatment with pembrolizumab. Sacituzumab govitecan, a Trop-2-directed antibody-drug conjugate with a topoisomerase I inhibitor payload, improved progression-free survival (PFS) and overall survival (OS) versus chemotherapy in patients with pre-treated metastatic TNBC. Moreover, preclinical data suggest that topoisomerase I inhibitors may enhance the effects of immune checkpoint inhibitors through activation of the cGAS-STING pathway. Here we describe the international randomized phase III AFT-65/ASCENT-05/OptimICE-RD trial, which evaluates the efficacy and safety of sacituzumab govitecan plus pembrolizumab versus treatment of physician's choice (pembrolizumab ± capecitabine) among patients with early-stage TNBC with residual invasive disease after neoadjuvant therapy.Clinical Trial Registration: NCT05633654 (ClinicalTrials.gov)Other Study ID Number(s): Gilead Study ID: GS-US-595-6184Registration date: 1 December 2022Study start date: 12 December 2022Recruitment status: Recruiting.

AFT-65/ASCENT-05/OptimICE-RD is an ongoing clinical trial that is testing a new treatment combination for patients with stage II or III triple-negative breast cancer (TNBC). Stage II­III means the cancer is confined to the breast and/or nearby lymph nodes and can be surgically removed. However, there remains a risk that the cancer could recur after surgery. To reduce this risk, patients with stage II­III TNBC receive anti-cancer medication before and after surgery. For some patients, receipt of anti-cancer medication before surgery produces a pathologic complete response (pCR), meaning there is no observable cancer left behind at surgery. Patients with a pCR have a lower risk of recurrence than patients with residual disease.The AFT-65/ASCENT-05/OptimICE-RD trial includes people with stage II-III TNBC who have residual cancer after completing their course of pre-surgery anti-cancer medication. All participants have any remaining cancer in their breast and/or lymph nodes removed surgically, after which they are randomly assigned to receive one of two treatments. The experimental therapy consists of pembrolizumab along with a medication called sacituzumab govitecan, which kills cancer cells directly and may strengthen the anti-cancer immune response. Pembrolizumab strengthens the anti-cancer immune response, so the hypothesis of this trial is that the two medications will be more effective together. The control therapy consists of pembrolizumab, alone or in combination with a chemotherapy medication called capecitabine, which is the current standard of care. To study the effectiveness of each treatment, the researchers are following up with all participants to learn if and when their breast cancer returns.

Tumor microenvironment immunomodulation by nanoformulated TLR 7/8 agonist and PI3k delta inhibitor enhances therapeutic benefits of radiotherapy.

Infiltration of immunosuppressive cells into the breast tumor microenvironment (TME) is associated with suppressed effector T cell (Teff) responses, accelerated tumor growth, and poor clinical outcomes. Previous studies from our group and others identified infiltration of immunosuppressive myeloid-derived suppressor cells (MDSCs) and regulatory T cells (Tregs) as critical contributors to immune dysfunction in the orthotopic triple-negative breast cancer (TNBC) tumor model limiting the efficacy of adoptive cellular therapy. However, approaches to target these cells specifically in the TME are currently lacking. To overcome this barrier, polymeric micelles nanoparticles (PMNPs) were used for co-delivery of small molecule drugs activating Toll-like receptors 7 and 8 (TLR7/8) and inhibiting PI3K delta. The immunomodulation of the TME by TLR7/8 agonist and PI3K inhibitor altered macrophage polarization, reduced MDSC accumulation and selectively decreased tissue-resident Tregs in the TME, while enhancing the T and B cell adaptive immune response. PMNPs significantly enhanced the anti-tumor activity of local radiation therapy (RT) in mice bearing orthotopic TNBC tumors compared to RT alone. Taken together, these data demonstrate that RT combined with a nanoformulated immunostimulant restructured the TME and has promising potential for future translation combined with RT for patients with TNBC.

The VEGF-Hypoxia Signature Is Upregulated in Basal-like Breast Tumors from Women of African Ancestry and Associated with Poor Outcomes in Breast Cancer.

PURPOSE: Black women experience the highest breast cancer mortality rate compared with women of other racial/ethnic groups. To gain a deeper understanding of breast cancer heterogeneity across diverse populations, we examined a VEGF-hypoxia gene expression signature in breast tumors from women of diverse ancestry. EXPERIMENTAL DESIGN: We developed a NanoString nCounter gene expression panel and applied it to breast tumors from Nigeria (n = 182) and the University of Chicago (Chicago, IL; n = 161). We also analyzed RNA sequencing data from Nigeria (n = 84) and The Cancer Genome Atlas (TCGA) datasets (n = 863). Patient prognosis was analyzed using multiple datasets. RESULTS: The VEGF-hypoxia signature was highest in the basal-like subtype compared with other subtypes, with greater expression in Black women compared with White women. In TCGA dataset, necrotic breast tumors had higher scores for the VEGF-hypoxia signature compared with non-necrosis tumors (P < 0.001), with the highest proportion in the basal-like subtype. Furthermore, necrotic breast tumors have higher scores for the proliferation signature, suggesting an interaction between the VEGF-hypoxia signature, proliferation, and necrosis. T-cell gene expression signatures also correlated with the VEGF-hypoxia signature when testing all tumors in TCGA dataset. Finally, we found a significant association of the VEGF-hypoxia profile with poor outcomes when using all patients in the METABRIC (P < 0.0001) and SCAN-B datasets (P = 0.002). CONCLUSIONS: These data provide further evidence for breast cancer heterogeneity across diverse populations and molecular subtypes. Interventions selectively targeting VEGF-hypoxia and the immune microenvironment have the potential to improve overall survival in aggressive breast cancers that disproportionately impact Black women in the African Diaspora.

Gene expression biomarkers differentiate overall survival of colorectal cancer upon targeted therapies.

While monoclonal antibody-based targeted therapies have substantially improved progression-free survival in cancer patients, the variability in individual responses poses a significant challenge in patient care. Therefore, identifying cancer subtypes and their associated biomarkers is required for assigning effective treatment. In this study, we integrated genotype and pre-treatment tissue RNA-seq data and identified biomarkers causally associated with the overall survival (OS) of colorectal cancer (CRC) patients treated with either cetuximab or bevacizumab. We performed enrichment analysis for specific consensus molecular subtypes (CMS) of colorectal cancer and evaluated differential expression of identified genes using paired tumor and normal tissue from an external cohort. In addition, we replicated the causal effect of these genes on OS using validation cohort and assessed their association with the Cancer Genome Atlas Program data as an external cohort. One of the replicated findings was WDR62, whose overexpression shortened OS of patients treated with cetuximab. Enrichment of its over expression in CMS1 and low expression in CMS4 suggests that patients with CMS4 subtype may drive greater benefit from cetuximab. In summary, this study highlights the importance of integrating different omics data for identifying promising biomarkers specific to a treatment or a cancer subtype.

Generative Adversarial Networks Accurately Reconstruct Pan-Cancer Histology from Pathologic, Genomic, and Radiographic Latent Features.

Artificial intelligence models have been increasingly used in the analysis of tumor histology to perform tasks ranging from routine classification to identification of novel molecular features. These approaches distill cancer histologic images into high-level features which are used in predictions, but understanding the biologic meaning of such features remains challenging. We present and validate a custom generative adversarial network - HistoXGAN - capable of reconstructing representative histology using feature vectors produced by common feature extractors. We evaluate HistoXGAN across 29 cancer subtypes and demonstrate that reconstructed images retain information regarding tumor grade, histologic subtype, and gene expression patterns. We leverage HistoXGAN to illustrate the underlying histologic features for deep learning models for actionable mutations, identify model reliance on histologic batch effect in predictions, and demonstrate accurate reconstruction of tumor histology from radiographic imaging for a 'virtual biopsy'.

Research autopsy programmes in oncology: shared experience from 14 centres across the world.

While there is a great clinical need to understand the biology of metastatic cancer in order to treat it more effectively, research is hampered by limited sample availability. Research autopsy programmes can crucially advance the field through synchronous, extensive, and high-volume sample collection. However, it remains an underused strategy in translational research. Via an extensive questionnaire, we collected information on the study design, enrolment strategy, study conduct, sample and data management, and challenges and opportunities of research autopsy programmes in oncology worldwide. Fourteen programmes participated in this study. Eight programmes operated 24 h/7 days, resulting in a lower median postmortem interval (time between death and start of the autopsy, 4 h) compared with those operating during working hours (9 h). Most programmes (n = 10) succeeded in collecting all samples within a median of 12 h after death. A large number of tumour sites were sampled during each autopsy (median 15.5 per patient). The median number of samples collected per patient was 58, including different processing methods for tumour samples but also non-tumour tissues and liquid biopsies. Unique biological insights derived from these samples included metastatic progression, treatment resistance, disease heterogeneity, tumour dormancy, interactions with the tumour micro-environment, and tumour representation in liquid biopsies. Tumour patient-derived xenograft (PDX) or organoid (PDO) models were additionally established, allowing for drug discovery and treatment sensitivity assays. Apart from the opportunities and achievements, we also present the challenges related with postmortem sample collections and strategies to overcome them, based on the shared experience of these 14 programmes. Through this work, we hope to increase the transparency of postmortem tissue donation, to encourage and aid the creation of new programmes, and to foster collaborations on these unique sample collections. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.