Jeremiah Wala

The spatial arrangement of immune cells in the tumor microenvironment (TME) varies widely, from dispersed to clustered and tumor-excluded to infiltrating. Multiplexed spatial profiling is an effective means of characterizing tumor-infiltrating lymphocytes and immune complexes such as tertiary lymphoid structures (TLS) in the TME. However, few approaches have been described for objectively parametrizing patterns of immune organization and assessing their association with biological or clinical variables. This makes it difficult to evaluate whether a set of tumors is relatively immunologically cold or hot. In this study, we describe an intuitive set of statistical tools (available in the R package, tlsR) for characterizing lymphocyte patterns in the TME of solid cancers. We applied tlsR to primary prostate cancer, which is often described as immunologically “cold.” Using a cohort of 29 radical prostatectomy specimens stratified into low Gleason grade (LGG; n = 15) and high Gleason grade (HGG; n = 14), we showed that HGG prostate cancer is significantly more infiltrated than LGG prostate cancer, with lymphocytes organized into B or T cell–enriched immune clusters (IC). A subset of these ICs had the B- and T-cell zonation and follicular dendritic cells characteristic of bona fide TLSs. HGGs were also enriched with ICs containing precursors of exhausted T cells and proliferating B cells, and their tumor compartments harbored granzyme B+ cytotoxic T cells in contact with cancer cells. Thus, far from being cold, a subset of HGG prostate cancer has features associated with active immune surveillance, a finding with implications for emerging prostate cancer immunotherapies.

All supplementary tables and figures.

Purpose:Computational pathology has emerged as an attractive option for improving risk stratification in prostate cancer, but most approaches either lack interpretability or focus solely on tumor morphology. We aimed to identify an interpretable, immune microenvironment–derived computational pathology biomarker for prostate cancer. Experimental Design:We identified two cohorts (discovery and validation) with M0 prostate cancer (n = 490) who were treated with radical prostatectomy, with hematoxylin and eosin–stained whole-slide images (WSI) and data on distant metastasis (DM). We identified a third cohort from The Cancer Genome Atlas with M0 prostate cancer (n = 326) with prostatectomy WSIs and bulk sequencing. Immune cells were identified from WSIs using a deep learning method (CellViT), and spatially dense immune clusters were quantified using density-based spatial clustering of applications with noise (DBSCAN). CIBERSORTx was utilized for immune cell deconvolution and TRUST4 for immune receptor repertoire reconstruction. Results:Median follow-up was 12.6 years (discovery) and 8.1 years (validation). Fourteen percent (n = 37, discovery) and seventeen percent (n = 38, validation) had Gleason 8 to 10 disease. Immune cell abundance was not associated with DM. In discovery, increased immune cluster was associated with decreased risk of DM for Gleason 8 to 10 (adjusted hazard ratio, 0.42; 95% confidence interval, 0.19–0.93) but not Gleason 6 to 7 (1.26, 0.77–2.05; Pint = 0.020), with similar results in validation (Gleason 8–10: 0.60, 0.37–0.98; Gleason 6–7: 1.19, 0.74–1.91; Pint = 0.043). In Gleason 8 to 10 but not 6 to 7, high-cluster samples were enriched for CD8+ T cells, activated memory CD4+ T cells, regulatory T cells (P ≤ 0.037), and clonal T-cell populations (P ≤ 0.039). Conclusions:These findings propose immune spatial clustering as a novel, interpretable computational pathology biomarker and provide insight into the unique immune features of high-grade prostate cancer.

Purpose: Computational pathology has emerged as an attractive option for improving risk stratification in prostate cancer, but most approaches either lack interpretability or focus solely on tumor morphology. We aimed to identify an interpretable, immune microenvironment–derived computational pathology biomarker for prostate cancer. Experimental Design: We identified two cohorts (discovery and validation) with M0 prostate cancer (n = 490) who were treated with radical prostatectomy, with hematoxylin and eosin–stained whole-slide images (WSI) and data on distant metastasis (DM). We identified a third cohort from The Cancer Genome Atlas with M0 prostate cancer (n = 326) with prostatectomy WSIs and bulk sequencing. Immune cells were identified from WSIs using a deep learning method (CellViT), and spatially dense immune clusters were quantified using density-based spatial clustering of applications with noise (DBSCAN). CIBERSORTx was utilized for immune cell deconvolution and TRUST4 for immune receptor repertoire reconstruction. Results: Median follow-up was 12.6 years (discovery) and 8.1 years (validation). Fourteen percent (n = 37, discovery) and seventeen percent (n = 38, validation) had Gleason 8 to 10 disease. Immune cell abundance was not associated with DM. In discovery, increased immune cluster was associated with decreased risk of DM for Gleason 8 to 10 (adjusted hazard ratio, 0.42; 95% confidence interval, 0.19–0.93) but not Gleason 6 to 7 (1.26, 0.77–2.05; Pint = 0.020), with similar results in validation (Gleason 8–10: 0.60, 0.37–0.98; Gleason 6–7: 1.19, 0.74–1.91; Pint = 0.043). In Gleason 8 to 10 but not 6 to 7, high-cluster samples were enriched for CD8+ T cells, activated memory CD4+ T cells, regulatory T cells (P ≤ 0.037), and clonal T-cell populations (P ≤ 0.039). Conclusions: These findings propose immune spatial clustering as a novel, interpretable computational pathology biomarker and provide insight into the unique immune features of high-grade prostate cancer.

Fast, reproducible detection and quantitative analysis of tertiary lymphoid structures (TLS) in multiplexed tissue imaging. Implements Independent Component Analysis Trace (ICAT) index, local Ripley's K scanning, automated K Nearest Neighbor (KNN)-based TLS detection, and T-cell clusters identification as described in Amiryousefi et al. (2025) .

The spatial arrangement of immune cells in the tumor microenvironment (TME) varies widely, from dispersed to clustered and tumor excluded to infiltrating. Multiplexed spatial profiling is an effective means of characterizing tumor-infiltrating lymphocytes (TILs) and immune complexes such as tertiary lymphoid structures (TLS) in the TME. However, few approaches have been described for objectively parametrizing patterns of immune organization and assessing their association with biological or clinical variables. This makes it difficult to evaluate whether a set of tumors is relatively immunologically cold or hot. Here we describe an intuitive set of statistical tools (available in the R package, tlsR ) for characterizing lymphocyte patterns in the TME of solid cancers. We apply tlsR to primary prostate cancer (PCa), which is often described as immunologically ‘cold’. Using a cohort of 29 radical prostatectomy specimens stratified into low Gleason-grade (LGG; n=15) and high Gleason-grades (HGG; n =14) we show that HGG PCa is significantly more infiltrated than LGG PCa with lymphocytes organized into B cell or T cell enriched immune clusters (BICs and TICs). A subset of these ICs have the B and T cell zonation and follicular dendritic cells characteristic of a bona fide TLS. HGGs are also enriched with ICs containing precursor exhausted T cells (T _pex ) and proliferating B cells and their tumor compartments harbor granzyme-B ⁺ cytotoxic T cells in contact with cancer cells. Thus, far from being cold, a subset of HGG PCa has features associated with active immune surveillance, a finding with implications for emerging PCa immunotherapies.

Predicting the progression of solid cancers based solely on genetics is challenging due to the influence of the tumor microenvironment (TME). For colorectal cancer (CRC), tumors deficient in mismatch repair (dMMR) are more immune infiltrated than mismatch repair proficient (pMMR) tumors and have better prognosis following resection. Here we quantify features of the CRC TME by combining spatial profiling with genetic analysis and release our findings via a spatially enhanced version of cBioPortal that facilitates multi-modal data exploration and analysis. We find that ∼20% of pMMR tumors exhibit similar levels of T cell infiltration as dMMR tumors and that this is associated with better survival but not any specific somatic mutation. These T cell-infiltrated pMMR (tipMMR) tumors contain abundant cells expressing PD1 and PDL1 as well as T regulatory cells, consistent with a suppressed immune response. Thus, like dMMR CRC, tipMMR CRC may benefit from immune checkpoint inhibitor therapy. SIGNIFICANCE pMMR tumors with high T cell infiltration and active immunosuppression are identifiable with a mid-plex imaging assay whose clinical deployment might double the number of treatment-naïve CRCs eligible for ICIs. Moreover, the low tumor mutational burden in tipMMR CRC shows that MMR status is not the only factor promoting immune infiltration.

Structural variants (SVs) represent a mechanism by which cancer cells activate oncogenes or disrupt the function of genes with tumor suppressor roles. A recent study by the PCAWG Consortium investigated structural variants in 30 tumor types, identifying focal rearrangements in the oncogenic BRD4 gene in ovarian, endometrial and breast cancers. These rearrangements resulted in decreased BRD4 expression despite increased copy number, suggesting a novel mechanism to finetune gene over-expression. In this study, we show that focal deletions of BRD4 disrupt genomic regulatory regions and impact gene isoform expression in breast and ovarian tumors when compared to their expression across normal tissues. To determine the functional impact of these concomitant amplification and focal deletion events, we first leveraged open-reading-frame (ORF) screen data from 16 cancer cell lines, where we observed that overexpression of BRD4-long and BRD4-short isoforms is toxic for cancer cell growth. We confirmed these results in OVSAHO ovarian cancer cells, where overexpression of both isoforms significantly reduced tumor growth. Next, we mimicked the focal deletions occurring in BRD4 regulatory regions by CRISPR-Cas9 technology, and observed that their depletion functionally ablates tumor cell growth. We finally show that these focal deletions rescue ovarian carcinoma cells from the toxicity effects associated with gene overexpression, suggesting that global BRD4 gene expression levels must be fine tuned to ensure proper cancer cell proliferation. Our study provides experimental evidence for BRD4 deletions constituting the first example of a driver SV alteration reducing toxicity in cancer, therefore expanding the landscape of cancer progression mechanisms.

The Oncology Grand Rounds series is designed to place original reports published in the Journal into clinical context. A case presentation is followed by a description of diagnostic and management challenges, a review of the relevant literature, and a summary of the authors' suggested management approaches. The goal of this series is to help readers better understand how to apply the results of key studies, including those published in the Journal of Clinical Oncology, to patients seen in their own clinical practice. For generations, oncologists and urologists have used androgen deprivation therapy (ADT) to manage metastatic hormone-sensitive prostate cancer (mHSPC). Until recently, ADT monotherapy was standard. Within the past decade, a series of trials have clearly demonstrated improved outcomes with a more aggressive up-front approach. Doublet intensification therapy, involving either ADT plus docetaxel or ADT plus any of several second-generation oral androgen-receptor pathway inhibitors (ARPIs), provide considerable survival advantages compared with ADT alone. In 2022, two trials, PEACE-1 and ARASENS, demonstrated the potential of triplet therapy, adding an ARPI to an ADT-docetaxel doublet. In the Original Report that accompanies this article, the authors provide a post hoc analysis of ARASENS (ADT plus docetaxel, with or without darolutamide), identifying the subpopulations of patients with mHSPC who might benefit most from a triplet regimen. They segment the ARASENS cohort by disease volume and disease risk profile, finding that triplet therapy is associated with improved outcomes regardless of category (although with limited power in the low-volume cohort). Meanwhile, trials are ongoing examining the role of radiotherapy (RT) in mHSPC, a modality previously reserved for localized disease or isolated, symptomatic metastases. Here, we present a mHSPC case and discuss our approach to mHSPC considering recent studies. We recommend triplet therapy for patients who are suitable candidates for chemotherapy, especially for patients with high-volume disease. We also favor aggressive use of RT, when feasible, for patients with low-volume mHSPC.