bims-tuinly 2024-12-08 papers

bims-tuinly

Biomed News

on Tumor-infiltrating lymphocytes therapy

Issue of 2024–12–08
eight papers selected by
Pierpaolo Ginefra, Ludwig Institute for Cancer Research

Prognostic role of tumor-infiltrating lymphocytes in gastric cancer: A systematic review and meta-analysis.
Analyzing functional heterogeneity of effector cells for enhanced adoptive cell therapy applications.
A non-inferiority, phase III trial of gemcitabine plus capecitabine versus gemcitabine plus carboplatin as first-line therapy and tumor-infiltrating lymphocytes as a prognostic biomarker in patients with advanced triple-negative breast cancer.
The analytical and clinical validity of AI algorithms to score TILs in TNBC: can we use different machine learning models interchangeably?
Differential predictive value of resident memory CD8+T cell subpopulations in patients with non-small-cell lung cancer treated by immunotherapy.
CD45RO-Positive Memory T-Cell Density in the Tumoral Core and Invasive Margin Predict Long-Term Survival in Esophageal Squamous Cell Carcinoma.
Evaluation of the 'Sip Til Send' regimen before elective caesarean delivery using bedside gastric ultrasound.
The efficacy and safety of relatlimab/nivolumab combination therapy in patients with advanced melanoma: a systematic review.

Clin Res Hepatol Gastroenterol. 2024 Nov 29. pii: S2210-7401(24)00231-6. [Epub ahead of print]49(1): 102510

Prognostic role of tumor-infiltrating lymphocytes in gastric cancer: A systematic review and meta-analysis.

Xiaoqing Cao, Yurou Kang, Ping Tai, Pei Zhang, Xin Lin, Fei Xu, Zhenlin Nie, Bangshun He.

   BACKGROUND: To analyze the relationship between tumor-infiltrating lymphocytes (TILs) subtypes and infiltration locations and the prognosis of gastric cancer (GC) patients.
METHODS: Eligible articles were obtained through systematic retrieval and rigorous screening, collecting study information and extracting hazard ratio (HR), 95 % confidence interval (CI) for pooled analyses of disease-free survival (DFS) and overall survival (OS).
RESULTS: Higher CD4+ TILs were correlated with favorable OS (HR=0.79, 95 %CI: 0.66-0.94, P = 0.009), the similar results were observed in tumor center and in infiltration margin. Higher CD8+ TILs prolonged DFS (HR=0.69, 95 %CI: 0.51-0.95, P = 0.02) and OS (HR=0.96, 95 %CI: 0.94-0.99, P = 0.006); For OS, tumor center and infiltration margin groups showed positive results. Neither the overall analysis nor the subgroup analyses indicated that the level of FOXP3+ TILs was associated with prognosis (DFS: HR=0.89, 95 %CI: 0.66-1.19, P = 0.42; OS: HR=0.98, 95 %CI: 0.85-1.13, P = 0.75). Pooled results revealed that higher CD3+ TILs were correlated with favorable DFS (HR=0.69, 95 %CI: 0.56-0.84, P = 0.0003) but not OS (HR=1.00, 95 %CI: 0.99-1.01, P = 0.48).
CONCLUSIONS: High infiltrating CD3+, CD4+, CD8+ T cells prolong survival, and FOXP3+ subset is not related to prognosis in GC. For CD4+ and CD8+, positive correlations between the infiltration level and OS were present in tumor center and infiltration margin groups.

Keywords:  Gastric cancer; Immunotherapy; Meta-analysis; Prognosis; Tumor-infiltrating lymphocytes

DOI:  https://doi.org/10.1016/j.clinre.2024.102510
Immunooncol Technol. 2024 Dec;24 100738

Analyzing functional heterogeneity of effector cells for enhanced adoptive cell therapy applications.

A C Kiel Rasmussen, T M Hulen, D L Petersen, M J Jacobsen, M J Mikkelsen, Ö Met, M Donia, C A Chamberlain, P Mouritzen.

  Cellular effector function assays traditionally rely on bulk cell populations that mask complex heterogeneity and rare subpopulations. The Xdrop® droplet technology facilitates high-throughput compartmentalization of viable single cells or single-cell pairs in double-emulsion droplets, enabling the study of single cells or cell-cell interactions at an individual level. Effector cell molecule secretion and target cell killing can be evaluated independently or in combination. Compatibility with a wide range of commercial assay reagents allows for single-cell level readouts using common laboratory techniques such as flow cytometry or microscopy. Moreover, individual cells of interest can be viably isolated for further investigation or expansion. Here we demonstrate the application of the double-emulsion droplet technology with a range of cell types commonly utilized for adoptive cell therapy of cancer: natural killer cells, blood-derived T cells, tumor-infiltrating lymphocytes, and chimeric antigen receptor T cells. Single-cell compartmentalization offers unparalleled resolution, serving as a valuable tool for advancing the development and understanding of cellular therapy products.

Keywords:  Xdrop; cancer immunotherapy; cell characterization; cell therapy; microfluidics; single-cell analysis

DOI:  https://doi.org/10.1016/j.iotech.2024.100738
Ther Adv Med Oncol. 2024 ;16 17588359241240304

A non-inferiority, phase III trial of gemcitabine plus capecitabine versus gemcitabine plus carboplatin as first-line therapy and tumor-infiltrating lymphocytes as a prognostic biomarker in patients with advanced triple-negative breast cancer.

Xiaodong Liu, Weipeng Zhao, Yongsheng Jia, Yehui Shi, Xu Wang, Shufen Li, Pin Zhang, Chen Wang, Chunfang Hao, Zhongsheng Tong.

   Background: Gemcitabine plus capecitabine (GX) shows survival benefit and manageable safety in patients with advanced triple-negative breast cancer (TNBC) but there is a paucity of phase III trial evidence. We aimed to compare the efficacy and safety of GX with gemcitabine plus carboplatin (GC) as first-line treatment for patients with advanced TNBC and validate the prognostic value of tumor-infiltrating lymphocytes (TILs).
Methods: Patients with advanced TNBC were randomly assigned 1:1 to receive gemcitabine (1000 mg/m2) on days 1 and 8 plus oral capecitabine (1000 mg/m2 twice a day) on days 1-14, or gemcitabine (1000 mg/m2) on days 1 and 8 plus carboplatin area under curve 2 on days 1 and 8. The primary endpoint was progression-free survival (PFS). TILs were analyzed by immunohistochemistry. The margin used to establish non-inferiority was 1.2.
Results: In all, 187 patients were randomly assigned, with 93 in GX and 94 in GC. Median PFS was 6.1 months in the GX arm compared with 6.3 months in the GC arm. The hazard ratio for PFS was 1.148, and a 95% CI was 0.856-1.539, exceeding the non-inferiority margin of 1.2. The median overall survival (OS) was 21.0 months in the GX arm compared with 21.5 months in the GC arm. The safety profile for the GX regimen was superior to the GC regimen, especially regarding hematological toxicity. Patients with high CD8+ TILs had significantly longer PFS and OS compared with patients with low CD8+ TILs. In the high CD8+ TIL group, the GC arm had prolonged PFS and OS compared with the GX arm.
Conclusion: The trial did not meet the prespecified criteria for the primary endpoint of PFS in patients with advanced TNBC. Moreover, the GC regimen showed better efficacy compared with the GX regimen in patients with high CD8+ TILs. However, the GX regimen should be considered in patients who cannot tolerate hematological toxicity.
Trial registration: ClinicalTrials.gov identifier: NCT02207335.

Keywords:  chemotherapy; gemcitabine plus capecitabine; gemcitabine plus carboplatin; triple-negative breast cancer; tumor-infiltrating lymphocytes

DOI:  https://doi.org/10.1177/17588359241240304
EClinicalMedicine. 2024 Dec;78 102928

The analytical and clinical validity of AI algorithms to score TILs in TNBC: can we use different machine learning models interchangeably?

Joan Martínez Vidal, Nikos Tsiknakis, Johan Staaf, Ana Bosch, Anna Ehinger, Emma Nimeus, Roberto Salgado, Yalai Bai, David L Rimm, Johan Hartman, Balazs Acs.

   Background: Pathologist-read tumor-infiltrating lymphocytes (TILs) have showcased their predictive and prognostic potential for early and metastatic triple-negative breast cancer (TNBC) but it is still subject to variability. Artificial intelligence (AI) is a promising approach toward eliminating variability and objectively automating TILs assessment. However, demonstrating robust analytical and prognostic validity is the key challenge currently preventing their integration into clinical workflows.
Methods: We evaluated the impact of ten AI models on TILs scoring, emphasizing their distinctions in TILs analytical and prognostic validity. Several AI-based TILs scoring models (seven developed and three previously validated AI models) were tested in a retrospective analytical cohort and in an independent prospective cohort to compare prognostic validation against invasive disease-free survival endpoint with 4 years median follow-up. The development and analytical validity set consisted of diagnostic tissue slides of 79 women with surgically resected primary invasive TNBC tumors diagnosed between 2012 and 2016 from the Yale School of Medicine. An independent set comprising of 215 TNBC patients from Sweden diagnosed between 2010 and 2015, was used for testing prognostic validity.
Findings: A significant difference in analytical validity (Spearman's r = 0.63-0.73, p < 0.001) is highlighted across AI methodologies and training strategies. Interestingly, the prognostic performance of digital TILs is demonstrated for eight out of ten AI models, even less extensively trained ones, with similar and overlapping hazard ratios (HR) in the external validation cohort (Cox regression analysis based on IDFS-endpoint, HR = 0.40-0.47; p < 0.004).
Interpretation: The demonstrated prognostic validity for most of the AI TIL models can be attributed to the intrinsic robustness of host anti-tumor immunity (measured by TILs) as a biomarker. However, the discrepancies between AI models should not be overlooked; rather, we believe that there is a critical need for an accessible, large, multi-centric dataset that will serve as a benchmark ensuring the comparability and reliability of different AI tools in clinical implementation.
Funding: Nikos Tsiknakis is supported by the Swedish Research Council (Grant Number 2021-03061, Theodoros Foukakis). Balazs Acs is supported by The Swedish Society for Medical Research (Svenska Sällskapet för Medicinsk Forskning) postdoctoral grant. Roberto Salgado is supported by a grant from Breast Cancer Research Foundation (BCRF).

Keywords:  Artificial intelligence; Breast cancer; Deep learning; Machine learning; TILs; Tumor infiltrating lymphocytes

DOI:  https://doi.org/10.1016/j.eclinm.2024.102928
J Immunother Cancer. 2024 Dec 03. pii: e009440. [Epub ahead of print]12(12):

Differential predictive value of resident memory CD8+T cell subpopulations in patients with non-small-cell lung cancer treated by immunotherapy.

Léa Paolini, Thi Tran, Stéphanie Corgnac, Jean-Philippe Villemin, Marie Wislez, Jennifer Arrondeau, Ludger Johannes, Jonathan Ulmer, Louis-Victorien Vieillard, Joséphine Pineau, Alain Gey, Valentin Quiniou, Pierre Barennes, Hang Phuong Pham, Nadège Gruel, Milena Hasan, Valentina Libri, Sebastien Mella, Sixtine De Percin, Pascaline Boudou-Rouquette, Aziza Caidi, Isabelle Cremer, Hélène Blons, Karen Leroy, Pierre Laurent-Puig, Hortense De Saint Basile, Laure Gibault, Patrice Ravel, Fathia Mami-Chouaib, François Goldwasser, Elizabeth Fabre, Diane Damotte, Eric Tartour.

   BACKGROUND: A high density of resident memory T cells (TRM) in tumors correlates with improved clinical outcomes in immunotherapy-treated patients. In most clinical studies, TRM are defined by the CD103 marker. However, it is clearly established that not all TRM express CD103, but can be defined by other markers (CD49a, CD69, etc). The frequency of these subpopulations of TRM expressing or not CD103 varies according to the location of the cancer. Little is known about their functionality and their predictive impact on response to immunotherapy. In preclinical models, only some subpopulations of TRM are associated with cancer vaccine efficacy.
METHODS: Multiparametric cytometry analyses were used to demonstrate the presence of TRM subpopulations in the lung in mice after vaccination and in fresh ex vivo human non-small cell lung cancer (NSCLC). An analysis of the T-cell repertoire of these TRM was conducted to search for their relationships. Multiplex immunofluorescence techniques were used to quantify intratumor infiltration of TRM subpopulations in two cohorts of patients with NSCLC. The impact on the clinical outcome of the TRM tumor infiltration was also investigated.
RESULTS: We identified two main TRM subpopulations in tumor-infiltrating lymphocytes derived from patients with NSCLC: one co-expressing CD103 and CD49a (double positive (DP)), and the other expressing only CD49a (simple positive (SP)); both exhibiting additional TRM surface markers like CD69. Despite higher expression of inhibitory receptors, DP TRM exhibited greater functionality compared with SP TRM. Analysis of T-cell receptor (TCR) repertoire and expression of the stemness marker TCF1 revealed shared TCRs between populations, with the SP subset appearing more progenitor-like phenotype. In the training cohort, PD-L1 (Programmed Death-Ligand 1) and TCF1+CD8+T cells predict response to anti-PD-1. In patient with NSCLC validation cohorts, only DP TRM predicted PD-1 blockade response. Multivariate analysis, including various biomarkers associated with responses to anti-PD-(L)1, such as total CD8, TCF1+CD8+T cells, and PD-L1, showed that only intratumoral infiltration by DP TRM remained significant.
CONCLUSIONS: This study highlights the non-equivalence of TRM subpopulations. The population of TRM co-expressing CD103 and CD49a appears to be the most functional and has the most significant capacity for predicting response to immunotherapy in multivariate analysis in patients with NSCLC.

Keywords:  Lung Cancer; T cell; Tumor microenvironment - TME

DOI:  https://doi.org/10.1136/jitc-2024-009440
Ann Surg Oncol. 2024 Dec 05.

CD45RO-Positive Memory T-Cell Density in the Tumoral Core and Invasive Margin Predict Long-Term Survival in Esophageal Squamous Cell Carcinoma.

Toshiki Noma, Tomoki Makino, Kenji Ohshima, Kotaro Yamashita, Takuro Saito, Koji Tanaka, Kazuyoshi Yamamoto, Tsuyoshi Takahashi, Yukinori Kurokawa, Kiyokazu Nakajima, Eiichi Morii, Hidetoshi Eguchi, Yuichiro Doki.

BACKGROUND: The association between tumor-infiltrating lymphocytes and tumor immunity has long been recognized. Among T-cell types, CD45RO-positive memory T cells (CD45RO+) are reported to correlate with survival in several cancer types, but clinical evidence is lacking in esophageal squamous cell carcinoma (ESCC).
METHODS: In surgical specimens from 162 preoperatively untreated patients, immunohistochemistry for CD45RO was performed to evaluate the density of CD45RO+ in the tumor core (CT) and invasive margin (IM) using an auto-count method. Patients were classified into high- versus low-CD45RO+ groups based on CD45RO+ density in CT and IM separately and combined. The relationship between CD45RO+ density and clinicopathological factors, including prognosis, was evaluated.
RESULTS: Average CD45RO+ density was 133/mm2 in CT and 372/mm2 in IM. No significant differences in clinicopathological factors according to high- versus low-CD45RO+ scores were identified. Using CT scores, the CD45RO+-high group had a better 5-year overall survival (OS) rate (77.2% vs. 54.7% CD45RO+-low, P = 0.0433), but OS rates did not differ statistically between the two groups by IM scores (75.7% vs. 50.3%, P = 0.0576). Using immunohistochemical scores for CT+IM, the survival difference was significant, with a 5-year OS rate of 73.7% for the CD45RO+-high group versus 46.3% for the CD45RO+-low group (P = 0.0141). Multivariate analysis identified CD45RO+ CT+IM density as an independent prognostic variable in OS (hazard ratio 2.27, 95% confidence interval 1.43-3.62, P = 0.0006).
CONCLUSIONS: Density of CD45RO+ expression in the CT and IM might be a predictor of long-term survival in ESCC.

DOI: https://doi.org/10.1245/s10434-024-16530-z
Eur J Anaesthesiol. 2025 Jan 01. 42(1): 80

Evaluation of the 'Sip Til Send' regimen before elective caesarean delivery using bedside gastric ultrasound.

Mahmut Sami Tutar, Munise Yildiz, Betul Kozanhan.

DOI: https://doi.org/10.1097/EJA.0000000000001976
Arch Dermatol Res. 2024 Dec 05. 317(1): 65

The efficacy and safety of relatlimab/nivolumab combination therapy in patients with advanced melanoma: a systematic review.

Saba Hasanzadeh, Parisa Farokh, Fatemeh Vazifeh, Golsa Sadat Hosseini, Leila Rezaei, Mozhgan Ghaedrahmati, Zahra Razaghi, Mostafa Rezaei Tavirani, Reza M Robati.

  Finding a treatment approach with high efficacy and minimal adverse reactions for advanced melanoma is still challenging. This study aimed to review and summarize available evidence regarding the effectiveness of the newly FDA-approved combination therapy of Relatmlimab and Nivolumab in patients with advanced melanoma and its comorbidities. We searched MEDLINE, EMBASE, and Cochrane Library for studies published in any language till 29/11/2023. We used the following Mesh and Emtree words, "melanoma" AND "relatlimab" AND "nivolumab". We screened 398 articles and included two single-arm clinical trials (N = 2) and one randomized clinical trial (RCT) (N = 1). In conclusion, The relatlimab/nivolumab combination therapy showed promising results for advanced melanoma patients. However, further research and longer follow-up periods are needed to compare it with previous treatments and validate its long-term effectiveness and safety.

Keywords:  Immunotherapy; Melanoma; Nivolumab; Relatlimab

DOI:  https://doi.org/10.1007/s00403-024-03579-9