Biology subjects

Uppaluri, R.

Publications and source records attributed to Uppaluri, R..

6 recordsLinked to original sources

bioRxiv2026

High-avidity TCR signaling induces a distinct KLR-positive exhaustion state in human tumor-infiltrating CD8 T cells associated with immunotherapy response

T cells adopt diverse states in human disease, with tumor-specific CD8 T cells serving as the quintessential example. These cells are critical for immunotherapy response, yet acquire hypofunctional states of exhaustion that impair treatment efficacy. While significant heterogeneity is observed among exhausted CD8 T cells (TEX), the mechanisms directing their unique phenotypes remain unresolved, limiting our efforts to augment TEX cell function. Here, we profile TEX cells in human head and neck squamous cell carcinoma (HNSCC) tumors and define a major mechanism regulating their cell state. With single-cell RNA and T cell receptor (TCR) sequencing of 106,667 tumor-infiltrating CD8 T cells, we define and validate three fundamental TEX subsets, each harboring dominant clonotypes: a progenitor subset (TPEX) and two intra-tumoral populations marked by intermediate (TEX-int) or high expression of inhibitory receptors, including killer cell lectin-like receptors, such as KLRC1/NKG2A (TEX-KLR). Using an in vitro model, we show that TCR avidity-dependent NFAT signaling governs an axis between the TEX-int and TEX-KLR states across human cancers, with high-avidity signaling driving the TEX-KLR state. Additionally, we uncover that interleukin-12 signaling selectively antagonizes high-avidity TEX-KLR-specific genes, despite broadly potentiating activation and cytotoxicity. Finally, we find that TEX-int and TEX-KLR cells are associated with anti-PD-1 response in HNSCC, with both of these cell types enriched near viable cancer cells following treatment. Together, these findings reveal that TCR avidity orchestrates tumor-infiltrating TEX cell states through NFAT signaling, a tunable axis that may be targeted to improve TEX cell function.

immunology↗

bioRxiv2024

Cancer vaccine attenuates carcinogen induced head and neck cancer with impaired early T cell response

Effective T cell immunotherapy requires understanding antigen-specific T cell development during tumorigenesis and immune surveillance. Here, we aimed to examine the dynamics of antigen-specific T cells from tumor initiation through progression in a tobacco carcinogen mimetic, 4-nitroquinoline-1-oxide (4NQO)-induced head and neck carcinogenesis model utilizing genetically engineered K5CreERT/+/ROSAOVA-GFP/p53fl/fl (KOG) mice. Our findings showed that early ovalbumin (OVA) expression via direct lingual tamoxifen (T) did not impact cancer development and survival, by comparing mice with tongue epithelium expressing OVA (KOG/T/OVA+) to those without OVA (KOG/T/OVA-) controlled by doxycycline. This equivalent tumor growth cannot be attributed to the loss of OVA expression. Intriguingly, although OVA-specific T cells were initially generated in tumor-draining lymph nodes (TDLN), they became undetectable 3 weeks after tamoxifen injection. Moreover, therapeutic anti-PD-1 was unable to restore OVA-specific T cells in TDLN and did not yield anti-tumor activity. Remarkably, OVA synthetic long peptide (SLP) vaccine induced OVA-specific T cells in KOG/T/OVA+ mice, and the combination of SLP vaccine and anti-PD-1 significantly reduced tongue tumor burden and prolonged survival. This study highlights the role of impaired endogenous antigen-specific T cell responses in immune resistance in head and neck cancer and the potential of cancer vaccines to improve outcomes.

cancer biology↗

bioRxiv2023

Ultrasensitive detection of circulating LINE-1 ORF1p as a specific multi-cancer biomarker

Improved biomarkers are needed for early cancer detection, risk stratification, treatment selection, and monitoring treatment response. While proteins can be useful blood-based biomarkers, many have limited sensitivity or specificity for these applications. Long INterspersed Element-1 (LINE-1, L1) open reading frame 1 protein (ORF1p) is a transposable element protein overexpressed in carcinomas and high-risk precursors during carcinogenesis with negligible detectable expression in corresponding normal tissues, suggesting ORF1p could be a highly specific cancer biomarker. To explore the potential of ORF1p as a blood-based biomarker, we engineered ultrasensitive digital immunoassays that detect mid-attomolar (10-17 M) ORF1p concentrations in patient plasma samples across multiple cancers with high specificity. Plasma ORF1p shows promise for early detection of ovarian cancer, improves diagnostic performance in a multi-analyte panel, and provides early therapeutic response monitoring in gastric and esophageal cancers. Together, these observations nominate ORF1p as a multi-cancer biomarker with potential utility for disease detection and monitoring. Statement of SignificanceLINE-1 ORF1p transposon protein is pervasively expressed in many cancers and a highly specific biomarker of multiple common, lethal carcinomas and their high-risk precursors in tissue and blood. Ultrasensitive ORF1p assays from as little as 25 L plasma are novel, rapid, cost-effective tools in cancer detection and monitoring.

cancer biology↗

bioRxiv2022

Epigenetic silencing by SMYD3 represses tumor intrinsic interferon response in HPV-negative squamous cell carcinoma of the head and neck.

Cancers often display immune escape, but the mechanisms and potential for reversibility are incompletely understood. Epigenetic dysregulation has been implicated in the immune escape of various cancer types. We have identified the epigenetic modifier SET and MYND-domain containing protein 3 (SMYD3) as a mediator of immune escape in human papilloma virus (HPV)- negative head and neck squamous cell carcinoma (HNSCC), an aggressive disease with poor prognosis and low response to immunotherapy with pembrolizumab, a programmed-death-1 (PD-1) targeting antibody. SMYD3 loss increased the sensitivity of HNSCC cancer cells to IFN-{beta}, resulting in upregulation of type I IFN response and antigen presentation machinery genes. We found that SMYD3 regulates the transcription of Ubiquitin-Like PHD And RING Finger Domain- Containing Protein 1 (UHRF1), a key epigenetic reader of trimethylated lysine 9 on histone H3 (H3K9me3), which binds to H3K9me3-enriched promoters of key immune-related genes and silences their expression. SMYD3 further maintains the repression of immune-related genes through the deposition of H4K20me3 within the gene body regions of these genes. In an anti-PD-1 immune checkpoint resistant syngeneic mouse model of HPV-negative HNSCC, Smyd3 depletion induced influx of CD8+ T-cells, upregulated PD-L1 and MHC class I molecules, and increased sensitivity to anti-PD-1 therapy. SMYD3 overexpression was associated with decreased CD8 T-cell infiltration in tumor samples from patients with HPV-negative HNSCC, and was associated with poor response to pembrolizumab. Overall, these data highlight a previously unreported function of SMYD3 as a master epigenetic regulator of anti-tumor immune response in HPV-negative HNSCC and provide a rationale for translational approaches combining SMYD3 depletion strategies with checkpoint blockade to overcome anti-PD-1 resistance in this devastating disease.

cancer biology↗

bioRxiv2022

SPACE-GM: geometric deep learning of disease-associated microenvironments from multiplex spatial protein profiles.

Multiplexed immunofluorescence imaging enables high-dimensional molecular profiling at subcellular resolution. However, learning disease-relevant cellular environments from these rich imaging data is an open challenge. We developed SPAtial CEllular Graphical Modeling (SPACE-GM), a geometric deep learning framework that flexibly models tumor microenvironments (TMEs) as cellular graphs. We applied SPACE-GM to 658 head-and-neck and colorectal human cancer samples assayed with 40-plex immunofluorescence imaging to identify spatial motifs associated with cancer recurrence and patient survival after immunotherapy. SPACE-GM is substantially more accurate in predicting patient outcomes than previous approaches for modeling spatial data using neighborhood cell-type compositions. Computational interpretation of the disease-relevant microenvironments identified by SPACE-GM generates insights into the effect of spatial dispersion of tumor cells and granulocytes on patient prognosis.

bioinformatics↗

bioRxiv2018

Development of a precision oncology single molecule molecular inversion probe (smMIP) panel using a community-consensus approach

Clinical targeted sequencing panels are important for identifying actionable variants for cancer patients, however, there are currently no strategies to create impartial and rationally-designed panels to accommodate rapidly growing knowledge within the field. Here we use the Clinical Interpretations of Variants in Cancer database (CIViC) in conjunction with single-molecule molecular inversion probe (smMIP) capture to identify and design probes targeting clinically relevant variants in cancer. In total, 2,027 smMIPs were designed to target 111 eligible CIViC variants. The total genomic region covered by the CIViC smMIPs reagent was 61.5 kb. When compared to existing genome or exome sequencing results (n = 27 cancer samples from 5 tumor types), CIViC smMIP sequencing demonstrated a 95% sensitivity for variant detection (n = 61/64 variants). Variant allele frequency for variants identified on both sequencing platforms were highly concordant (Pearson correlation = 0.885; n = 61 variants). Moreover, for individuals with paired tumor/normal samples (n = 12), 182 clinically relevant variants missed by original sequencing were discovered by CIViC smMIPs sequencing. This design paradigm demonstrates the utility of an open-sourced database built on attendant community contributions for each variant with peer-reviewed interpretations. Use of a public repository for variant identification, probe development, and variant annotation could provide a transparent approach to build a dynamic next-generation sequencing-based oncology panel.

bioinformatics↗