Kachergus, Jennifer M.

Background Tumor-infiltrating lymphocytes (TILs) are established determinants of clinical outcomes in breast cancer. 1–6 While stromal TILs (sTILs) are commonly evaluated due to easier scoring and higher interobserver reproducibility, intraepithelial TILs may provide additional insights into anti-tumor immunity. 7 We aimed to comprehensively characterize immunotype-associated cellular landscapes in triple-negative breast cancer (TNBC) and identify features associated with clinical outcomes. Methods 212 TNBC tumors were classified into three immunotypes based on immune infiltrate location and density: immune desert (ID), immune excluded (IE), and immune inflamed (IN). 8 Single-cell spatial transcriptomics was performed on 75 tumors to define the cellular composition and functional states of the tumor microenvironment across immunotypes. Findings were validated and integrated with bulk RNA sequencing data and clinical outcome datasets from FinXX, CALGB-40603, I-SPY 2, and Real-World Clinico-Genomic Data (RWCGD) cohorts. Results Patients with IN tumors had significantly improved outcomes compared with ID tumors. Despite high sTILs, IE tumors showed poor outcomes similar to ID tumors. Single-cell spatial analysis revealed that ID and IE tumors exhibited reduced major histocompatibility complex I/II expression and fewer tumor-resident plasmacytoid dendritic cells (pDCs) compared with IN tumors, which were enriched for interferon-alpha (IFNα) and interferon-gamma (IFNγ) responses. High IFN response scores were associated with favorable outcomes across multiple therapy types in independent datasets. Deconvolution of RWCGD bulk RNA-seq data confirmed that pDC abundance correlated with improved outcomes specifically in hormone receptor–negative subtypes. Conclusions Our study highlights pDCs and IFN signaling as hallmarks of effective anti-tumor immunity in TNBC. Immunotype-based profiling underscores the limited prognostic value of sTILs alone in immune-excluded tumors and supports pDCs and IFN pathways as potential biomarkers for prognosis and therapeutic development in TNBC.

Abstract Background: Most colorectal cancer (CRC) arises from polyps and is mainly prevented by polypectomy. The most important polyps to manage with colonoscopy are those with highest CRC risk- namely, advanced polyps (> 1cm, villous histology or high-grade dysplasia (HGD). Yet, 48% of advanced polyps recur within 1 to 3 years of removal, and up to 5% of advanced polyps under surveillance still progress to CRC. We performed this pilot study to investigate molecular and microenvironment heterogeneities of polyps and how they might impact their clinical behavior. Methods: GeoMx spatial transcriptomics was performed on FFPE tissues from three different polyp outcome phenotypes (POPs) including the polyp that does not recur (POP-NR), that recurs following polypectomy but cured by colonoscopy (POP-R) or the polyp despite polypectomy develops CRC at the polypectomy(ies) site (POP-CRC). Normal colon and polyp with low or HGD from the index polyp were assessed from 6 patients with POP-NR, 9 with POP-R and 12 with POP-CRC with a minimum of 2 follow up colonoscopies at 3-year intervals. Epithelium was identified as PanCK positive, and stroma identified as PanCK negative and positive nuclear staining. Cell type deconvolution was implemented using single-cell adult human intestinal tract catalogue (Elmentaite et al., https://www.gutcellatlas.org/). Differential gene expression (DEG), cell type abundance and functional enrichment analyses was performed using linear mixed effects model, and observations with p-value < 0.05 and log2FC >= |1| are reported. Results: The greatest number of DEGs were identified in stroma of the index POP-CRC compared to POP-NR polyps (n = 17 down and 11 upregulated genes), followed by epithelium of the index POP-CRC vs POP-NR polyps (n = 10 down and one upregulated gene(s)). Between the index POP-CRC and POP-R, epithelium showed downregulation of 7 genes, and upregulation of no genes. In stroma two genes were down and none upregulated. Four genes were downregulated in stroma of the index POP-R vs POP-NR polyp and 3 in epithelium, and one gene was upregulated in stroma and another in epithelium. MZT2B was upregulated in stroma of both the index POP-R (log2FC = 1.09, p-value = 0.0014) and POP-CRC (log2FC = 1.29, p-value = 0.0001) and has been implicated as a prognostic marker associated with worse prognosis in certain cancers. IgM and IgA plasma cells, proximal progenitors, MMP9+ inflammatory macrophages and myofibroblasts were found to be downregulated in epithelium of index POP-CRC and POP-R compared to POP-NR polyps; while microfold cells were downregulated in stroma of index POP-CRC and POP-R compared to POP-NR polyps. Conclusions: The stromal microenvironment and less so, epithelial features present in the index polyp differ based on a polyp’s future clinical behavior. The polyp-immune interaction warrants further study as a potential prevention target against polyp progression. Citation Format: Mrunal Dehankar, Lisa A. Boardman, Daniel O'Brien, E. Aubrey Thompson, Jennifer M. Kachergus, Ji Shi, Alexej Abyzov, Milovan Suvakov, Rondell P. Graham, Chen Wang. Stromal immune composition significantly contributes to adenomatous polyp recurrence or progression to cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4018.

Biological heterogeneity among different breast cancer (BC) subtypes results in markedly varying clinical outcomes. Identification and analysis of key gene biomarkers that are differentially regulated during radiation therapy (RT) may pose multiple clinical challenges for BC treatment. The purpose of the study is to identify and analyze the expression of key gene biomarkers and their networks that are differentially regulated after hypofractionated RT. Patients with BC (cT0-T2, N0, M0) were treated with hypofractionated whole breast RT 25 Gy in five fractions, 4 to 8 weeks before breast conservation surgery (BCS). Biopsy (pre-RT; n = 5) and surgical (post-RT; n = 14 or 15) BC tumor samples were used for NanoString targeted sequencing. We identified 165 and 244 differentially expressed genes (DEGs; p < 0.05) in BC tumor samples from BC patients post-RT using the nCounter BC360 and IO360 panels, respectively. Gene networks and pathway analysis revealed that RT increases the gene signature of tumor inflammation (TIS), cytotoxicity, and apoptosis, while downregulating the gene signatures of tumor cell proliferation, differentiation, and cell adhesion, and increases the claudin-low gene score. RT-induced mammary stemness and enhanced infiltration of stroma, mast, and macrophage cells in the BC tumor microenvironment (TME). Further, the nCounter IO360 (immuno-oncology) panel analysis validated the findings of BC360 and demonstrated that RT increased the myeloid inflammation signature and chemokine expression, modulated B, T, NK, and DC cell activities, and enhanced residual cancer burden (RCB) in BC tumors, thus creating an immunosuppressive TME. Collectively, RT sensitized BC tumors by increasing the gene signature of TIS, cytotoxicity, apoptosis, and mammary stemness. RT facilitated an immunosuppressive environment and increased RCB, suggesting that the therapeutic potential of RT is highly individualized for each patient based on their unique tumor biology, genetic makeup, and TME.

Objective To quantitatively examine immune cell markers and spatial distribution in human diabetic kidney disease (DKD) to enhance understanding of the inflammatory landscape contributing to injury. Maladaptive inflammation is an underrecognized contributor to DKD pathogenesis and progression and remains undertreated. Patients and methods NanoString GeoMx™ Digital Spatial Profiling technology targeted antibodies labeled with unique oligonucleotide barcode in kidney biopsy [DKD (n=5), tubulointerstitial nephritis (TIN; n=4), and normal (n=2)] with regions of interest selection of compartments (glomeruli, tubules, interstitium). Inflammation-related proteins were analyzed with differential expression through linear mixed modeling. Results Compared to normal tissue, inflammatory cell surface protein markers were increased in DKD tubules and interstitium. Markers of T cells (CD4, CD44), macrophages (CD68; proinflammatory), and antigen-presenting cells (APCs; CD40 and CD11c) were increased across all DKD compartments (vs. normal). Macrophage (CD163; prorepair) marker was increased in DKD tubules and interstitium (vs. normal). Fewer differences were observed in glomeruli for normal vs. DKD or TIN vs. DKD groups. CD66b+ (granulocytes) cell marker was higher in DKD (vs. TIN). As expected, TIN had higher levels of T cell and macrophage markers in tubules and interstitium (vs. DKD). Interestingly, CD34, a hematopoietic stem cell and endothelial cell marker, was lower in DKD tubules and interstitium (vs. normal) but higher in DKD (vs. TIN). Conclusion NanoString GeoMx DSP technology may fulfil a role in enhancing the understanding the inflammatory landscape engaged in DKD pathogenesis as well as measuring response to therapy. Moreover, additional investigations of CD34 progenitor cell depletion in DKD may be warranted.

Abstract Background The incidence of early onset breast cancers (BCs) has increased, paralleling rising trends in delayed childbearing. We hypothesize that a distinct postpartum BC (PPBC) subtype, identifiable by time since last birth (TSLB) and biomarker expression, contributes to this trend. Methods We applied GeoMx Digital Spatial Profiling (DSP) to measure associations between TSLB and 71 proteins in 640 BCs from women aged ≤40 years included in the Young Women’s Breast Cancer Study. We analyzed data using univariable linear regression and multivariable sliced inverse regression to account for higher order interactions among biomarkers. Results In keratin-rich segments, progesterone receptor (PR) (P = 1.00 × 10−4) and PTEN (P = 1.00 × 10−3) were associated with longer TSLB; multivariable analyses revealed positive associations for GZMB (P = 4.00 × 10−4), SMA (P = 1.00 × 10−4), and NF-1 (P = 1.00 × 10−3). In keratin-poor segments, univariable significant positive associations were found for PR (P = 2.00 × 10−4) and PTEN (P = 1.00 × 10−3), whereas CD20 (P = 3.00 × 10−4) and CTLA4 (P = 4.00 × 10−5) were negatively associated; multivariable significant associations were found for fibronectin (P = 3.00 × 10−5) and pan-Akt (P = 1.00 × 10−3). Associations persisted after adjustment for multiple comparisons and BC molecular subtypes. Associations including for PR, PTEN, and CD20 were strongest among women with the shortest TSLB. OPAL multiplex immunofluorescence assays for PR, PTEN, CD20, SMA, and CTLA4 replicated several DSP findings, particularly when stratified by subtype and with compartment matching. In TCGA, RNA species linked to proteins associated with TSLB correlated strongly with a T-cell exhaustion signature previously linked to poor prognosis among premenopausal women. Conclusion These data support PPBC as a biologically coherent phenotype defined by TSLB and biomarker profile, with potential implications for prevention and therapy.

Background: Discovering risk biomarkers in small benign breast disease (BBD) biopsies is constrained by scarce tissue and microanatomic heterogeneity of terminal duct lobular units (TDLUs). We tested whether tissue-sparing tissue microarray (TMA)–based Digital Spatial Profiling (DSP) can deliver reproducible, biologically coherent protein measurements across benign lobules and breast cancers (BCs), and how well DSP aligns with standard immunoassays. Methods: We performed a pilot using tissues from the Mayo Clinic BBD cohort using TMAs representing four contexts: terminal duct lobular units (TDLUs) from BBD biopsies preceding BC and matched BBD-controls, subsequent BCs, and BC-associated TDLUs. We profiled 79 proteins by DSP (37 retained after QC) and benchmarked against chromogenic IHC and OPAL immunofluorescence. Reproducibility was evaluated using intraclass correlation coefficients (ICCs), cross-platform agreement (weighted kappa), marker correlations, and mixed-effects models with false-discovery-rate (FDR) control. Results: We analyzed 368 BBD-TDLU cores (88 cases; 88 controls), 204 BC cores and 110 BC-associated TDLU cores. ICCs were highest in BC tissues, and lower in BC-associated TDLUs and BBD-TDLUs. Agreement was slight–to-fair in TDLUs but moderate (ER/PR) to substantial (BCL2) in BC. DSP recapitulated expected immunologic correlations (CD45 with T-cell, B-cell, and macrophage markers) and tissue-type gradients (BC > BC-associated TDLUs > BBD-TDLUs). Exploratory case–control differences in BBD-TDLUs did not persist after FDR control. Conclusions: TMA-based DSP is feasible in archival breast tissues and yields biologically coherent, cross-platform-benchmarked profiles that are particularly robust in BC, while conserving scarce TDLUS and clarifying current limits of single-marker risk stratification from benign lobules. These data provide a foundation for refined sampling and expanded panels in future TDLU-focused studies.

Abstract The highest risk for liver allograft rejection is within the first weeks to months after a liver transplant; however, while later-stage mechanisms are well described, the initial window at the moment of alloantigen influx (e.g., ~ 1 h post-reperfusion) remains unmapped. T-cell priming is initiated in lymph nodes, yet these sites are rarely profiled in humans and their relationship to rejection risk is unclear. To address this gap, we profiled paired pre- and ~ 1 h post-reperfusion hepatic draining lymph nodes from liver transplant recipients using multiplexed immunofluorescence and GeoMx whole-transcriptome profiling to identify features that predict rejection versus non-rejection. Early after reperfusion, CD4 + and CD8 + T cells became proximal to macrophages in rejection compared to dendritic cells in non-rejection, which also displayed an immunoregulatory-leaning profile marked by PD-1, IDO1, and CD39, suggesting that macrophages and dendritic cells differentially influence early T-cell alloimmunity. These results provide nodal targets for precise immune modulation.

Abstract Parkinson’s disease (PD) is the fastest growing neurodegenerative disease in the world1. Gastrointestinal (GI) dysfunction can occur decades before motor impairments and in up to 80% of individuals living with PD2,3,4. We investigated peripheral relationships that may underlie environmental contributions to mechanisms along the gut-blood axis that contribute to PD pathogenesis. Single-cell multiomic spatial molecular imaging (SMI) of colonic tissue localized inflammatory injury within epithelial cells that appear to be associated with iron mishandling in both inflammatory bowel disease (IBD) and PD biosamples. We found that both the single-cell SMI of RNA and protein revealed parallel cross-modal dysregulation in the gut epithelium, in both IBD and PD biosamples. These data are accompanied by plasma (PD) and stool (IBD) protein depletion of CCL22. Our findings suggest iron mishandling along the gut barrier likely contributes to systemic inflammation, which may be the catalyst that primes circulating immune cells to body-first PD pathogenesis.

Abstract Parkinson’s disease (PD) is the fastest growing neurodegenerative disease in the world 1 . Gastrointestinal (GI) dysfunction can occur decades before motor impairments and in up to 80% of individuals living with PD 2,3,4 . We investigated peripheral relationships that may underlie mechanisms along the gut-blood axis that contribute to PD pathogenesis. Single-cell multiomic spatial molecular imaging (SMI) of colonic tissue localized inflammatory injury within epithelial cells that appear to be associated with iron mishandling in both inflammatory bowel disease (IBD) and PD biosamples. We found that both the single-cell SMI of RNA and protein revealed parallel cross-modal dysregulation in the gut epithelium, in both IBD and PD biosamples. These data are accompanied by plasma (PD) and stool (IBD) protein depletion of CCL22. Our findings suggest iron mishandling along the gut barrier likely contributes to systemic inflammation, which may be the catalyst that primes circulating immune cells to body-first PD pathogenesis.

PURPOSE Predictive biomarkers to better tailor therapy for patients with early-stage human epidermal growth factor 2 (HER2)-positive breast cancer are a priority. We hypothesized that HER2 and immune-based biomarkers would be predictive of pathologic complete response (pCR) to preoperative trastuzumab/pertuzumab (HP). MATERIALS AND METHODS Patients with stage II/III, estrogen receptor (ER)-negative, HER2-positive breast cancer received neoadjuvant HP in the TBCRC026 clinical trial. The pCR after receiving HP alone was 22% (18/83). Tumor biopsies were performed at baseline. Secondary correlative objectives were to determine the relationship between HER2-based biomarkers and immune processes with pCR. NanoString code sets BC360 and IO360 were used to compare differential gene expression in baseline tumors that underwent pCR versus no pCR. NanoString GeoMx digital spatial profiling was used to assess immune protein abundance in intraepithelial and stromal segments. Stromal tumor-infiltrating lymphocytes and Ki67 were evaluated by hematoxylin and eosin and immunohistochemistry, respectively. RESULTS Intraepithelial HER2 protein abundance was significantly associated with pCR ( P = .001). Low HER2 abundance tumors were primarily basal-like, and essentially all (19/20) failed to achieve pCR. High HER2 abundance tumors that achieved pCR (14/51) exhibited a high degree of immune cell activity, whereas high HER2 abundance tumors that failed to achieve pCR tumors (37/51) were enriched for M-phase processes and epidermal growth factor receptor signaling. Baseline Ki67 was significantly higher in nonresponders ( P = .04). CONCLUSION ER-negative, HER2-positive breast cancer has unique molecular and immunologic features that may predict pCR after neoadjuvant HP. Validation of these potential biomarkers and composite biomarker analyses may guide design of future clinical trials.