Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer

Patil, Namrata; Nabet, Barzin Y.; Müller, Sören; Koeppen, Hartmut; Zou, Wei; Giltnane, Jennifer M.; Au-Yeung, Amelia; Srivats, Shyam; Cheng, Jason H.; Takahashi, Chikara; Almeida, Patrícia E. de; Chitre, Avantika S.; Grogan, Jane L.; Rangell, Linda; Jayakar, Sangeeta; Peterson, Maureen; Hsia, Allison W.; O’Gorman, William; Ballinger, Marcus; Banchereau, Romain; Shames, David S.

doi:10.1016/j.ccell.2022.02.002

Cited by 209 publications

(165 citation statements)

References 49 publications

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“…Additionally, the Mixed -Stromal High community that was enriched for various stromal states also showed modestly increased survival compared to more tumor-centric communities and ecotypes (Figure . 6.C). These findings align with previous studies showing that increased immune cell infiltration, particularly of CD8 T cells and plasma cells, portends better outcomes in a variety of cancer types [33][34][35] .…”

Section: B)supporting

confidence: 92%

“…These patients achieved strikingly higher overall survival than all other patients, with a 2-year overall survival of 71%. Indeed, tumor-infiltrating CD8 T and plasma cells have been shown to predict better survival in a variety of different solid tumor malignancies, especially in concert with immune checkpoint blockade 33,34 . It will be important to prospectively test whether these PDAC patients harboring immune-enriched tumors can be precisely selected using bulk RNA sequencing followed by digital deconvolution, and if their survival can be further enhanced with immune checkpoint blockade.…”

Section: Discussionmentioning

confidence: 99%

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High-dimensional deconstruction of pancreatic ductal adenocarcinoma identifies tumor microenvironmental communities associated with survival

Storrs¹,

Usmani²,

Chati

et al. 2022

Preprint

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Bulk and single-cell analyses of the pancreatic ductal adenocarcinoma (PDAC) tumor microenvironment (TME) have revealed a largely immunosuppressive milieu. Thus far, efforts to utilize insights from TME features to facilitate more effective therapeutics have largely failed. Here, we performed single-cell RNA sequencing (scRNA-seq) on a cohort of treatment-naive PDAC time-of-diagnosis endoscopic ultrasound-guided fine needle biopsy samples (n=22) and surgical samples (n=6), integrated with 3 public datasets (n=49), resulting in ~140,000 individual cells from 77 patients. Based on expression markers assessed by Seurat v3 and differentiation status assessed by CytoTRACE, we divided the resulting tumor cellular clusters into 5 molecular subtypes based on expression of previously reported marker genes: Basal, Mixed Basal/Classical, Classical Low, Classical High, and ADEX. We then queried these 5 tumor cell profiles, along with 15 scRNA-seq-derived tumor microenvironmental cellular profiles, in 391 bulk expression samples from 4 published datasets of localized PDAC with associated clinical metadata using CIBERSORTx. Through unsupervised clustering analysis of these 20 cell state fractions representing tumor, leukocyte and stromal cells, we identified 7 unique clustering patterns representing combinations of tumor cellular and microenvironmental cell states present in PDAC tumors. We termed these cell state patterns communities, and found them to correlate with overall survival, tumor ecotypes, and tumor cellular differentiation status. The community associated with worst overall survival contained basal tumor cells, exhausted CD4 and CD8 T cells, and was enriched for fibroblasts. In contrast, the highest overall survival was associated with a community high in immune cell enrichment. The differentiation state of tumor cells (assessed by CytoTRACE) was also correlated with survival in a dose-dependent fashion. Further, we identified a subset of PDAC samples that were significantly enriched for activated CD8 T and plasma cells that achieved a 2-year overall survival rate of 71%, suggesting we can identify PDAC patients with significantly improved prognoses and, potentially, higher sensitivity to immunotherapy. In summary, we identified novel tumor microenvironmental communities from high-dimensional analysis of PDAC RNA sequencing data that reveal new connections between tumor microenvironmental composition and patient survival that could lead to better upfront risk stratification and more personalized clinical decision-making.

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Section: B)supporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

High-dimensional deconstruction of pancreatic ductal adenocarcinoma identifies tumor microenvironmental communities associated with survival

Storrs¹,

Usmani²,

Chati

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…We should also note that, with the development of single-cell sequencing technique, special subtypes of immune and stromal cells have been identified in TME from ICB samples, which performed well in predicting responses toward ICB therapy (46,47). This could give us a new insight of prognostic prediction.…”

Section: Discussionmentioning

confidence: 89%

Plac1 Remodels the Tumor Immune Evasion Microenvironment and Predicts Therapeutic Response in Head and Neck Squamous Cell Carcinoma

Meng

Liu²,

Zhang³

et al. 2022

Front. Oncol.

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Head and neck squamous cell carcinoma (HNSCC or HNSC) is the sixth most common cancer worldwide. Placenta-specific 1 (Plac1) belongs to the cancer testis antigen family and is highly expressed in malignant cells in HNSC. However, the biological function and prognostic value of plac1 in HNSC are still unclear. In the current research, we performed a comprehensive analysis of plac1 using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) bulk RNA sequencing databases as well as a single-cell sequencing dataset. We constructed a 15-gene prognostic signature through screening plac1-related immunomodulators and validated its efficiency and accuracy in immunotherapy cohorts and a pancancer database. We found that plac1 expression level is a prognostic predictor of poor overall survival in patients with HNSC. Plac1 is associated with epithelial–mesenchymal transition and tumor invasion. Plac1 has a “dual immunosuppressive function” on tumor microenvironment. On one hand, plac1-positive cells promote extracellular matrix formation and suppress immune cell infiltration. On the other hand, plac1-positive cells enhance the interaction between dendritic cells and macrophages, which further suppresses antitumor immunity. Finally, we constructed a 15-gene prognostic signature, the efficiency and accuracy of which were validated in immunotherapy cohorts and a pancancer database. In conclusion, plac1 is a promising candidate biomarker for prognosis, a potential target for immunotherapy, and a novel point for studying the immunosuppressive mechanisms of the tumor microenvironment in HNSC.

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“…The expression of the TRN signature genes was heterogeneous between the different TRN subsets (Figure 6H). In order to analyze the prognostic and predictive value of the TRN signature, we used bulk RNA-seq data from pre-treatment tumors from POPLAR (Fehrenbacher et al, 2016) and OAK (Rittmeyer et al, 2017), two randomized clinical trials of anti-PD-L1 antibody (atezolizumab) versus chemotherapy (docetaxel) in NSCLC, representing the largest transcriptional collection in these settings (Patil et al, 2022). In total there were 891 patients of which 439 were treated with atezolizumab (316 LUAD and 123 LUSC) and 452 with docetaxel (312 LUAD and 139 LUSC).…”

Section: Resultsmentioning

confidence: 99%

“…TCGA drug response data was retrieved from (Moiso, 2021). Bulk RNA-seq samples from NSCLC patients treated with atezolizumab (anti-PD-L1) or docetaxel (chemotherapy) from the POPLAR (Fehrenbacher et al, 2016) and OAK (Rittmeyer et al, 2017) trials were retrieved using the accession numbers reported in (Patil et al, 2022). LCAM-consensus signature score was computed as described in (Leader et al, 2021) using the code provided in their GitHub repository.…”

Section: Star Methodsmentioning

confidence: 99%

High-resolution single-cell atlas reveals diversity and plasticity of tissue-resident neutrophils in non-small cell lung cancer

Salcher

Sturm

Horvath

et al. 2022

Preprint

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SUMMARYNon-small cell lung cancer (NSCLC) is characterized by molecular heterogeneity with diverse immune cell infiltration patterns, which has been linked to both, therapy sensitivity and resistance. However, full understanding of how immune cell phenotypes vary across different patient and tumor subgroups is lacking. Here, we dissect the NSCLC tumor microenvironment at high resolution by integrating 1,212,463 single-cells from 538 samples and 309 patients across 29 datasets, including our own dataset capturing cells with low mRNA content. Based on the cellular composition we stratified patients into immune deserted, B cell, T cell, and myeloid cell subtypes. Using bulk samples with genomic and clinical information, we identified specific cellular components associated with tumor histology and genotypes. Analysis of cells with low mRNA content uncovered distinct subpopulations of tissue-resident neutrophils (TRNs) that acquire new functional properties in the tissue microenvironment, providing evidence for the plasticity of TRNs. TRN-derived gene signature was associated with anti-PD-L1 treatment failure in a large NSCLC cohort.In briefSalcher, Sturm, Horvath et al. integrate single-cell datasets to generate the largest transcriptome atlas in NSCLC, refining patient stratification based on tumor immune phenotypes, and revealing associations of histological subtypes and genotypes with specific cellular composition patterns.Coverage of cells with low mRNA content by single-cell sequencing identifies distinct tissue-resident neutrophil subpopulations, which acquire new properties within the tumor microenvironment. Gene signature from tissue-resident neutrophils is associated with immune checkpoint inhibitor treatment failure. The integrated atlas is publicly available online (https://luca.icbi.at), allowing the dissection of tumor-immune cell interactions in NSCLC.HighlightsHigh-resolution single-cell atlas of the tumor microenvironment (TME) in NSCLC.Histological tumor subtypes and driver genes imprint specific cellular TME patterns.scRNA-seq of cells with low transcript count identifies distinct tissue-resident neutrophil (TRN) subpopulations and non-canonical functional properties in the TME niche.TRN gene signature identifies patients who are refractory to treatment with PD-L1 inhibitors.Abstract Figure

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Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer

Cited by 209 publications

References 49 publications

High-dimensional deconstruction of pancreatic ductal adenocarcinoma identifies tumor microenvironmental communities associated with survival

High-dimensional deconstruction of pancreatic ductal adenocarcinoma identifies tumor microenvironmental communities associated with survival

Plac1 Remodels the Tumor Immune Evasion Microenvironment and Predicts Therapeutic Response in Head and Neck Squamous Cell Carcinoma

High-resolution single-cell atlas reveals diversity and plasticity of tissue-resident neutrophils in non-small cell lung cancer

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