Predictive biomarkers of response to immunotherapy in triple-negative breast cancer – state of the art and future perspectives

Tancoš, Vladimír; Blichárová, Alžbeta

doi:10.48095/ccko202328

Cited by 2 publications

(4 citation statements)

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“…Recent advancements have made immunotherapy a useful tool in the treatment of various cancers. However, the inability of checkpoint inhibitors to show efficacy against tumors not expressing PD-L1 [50] has limited their efficacy in the setting of breast cancer; for example, up to 70% of women with triple-negative breast cancer have tumors expressing low levels of PD-L1 [51]. TAA's, such as survivin, provide the opportunity to develop immunotherapy, targeting a fixed set of peptides that could be broadly administered to breast cancer patients without the need for patient-specific tumor gene sequencing and personalized immunotherapy.…”

Section: Discussionmentioning

confidence: 99%

Survivin Expression in Luminal Breast Cancer and Adjacent Normal Tissue for Immuno-Oncology Applications

Wright,

Burkholz,

Zelinsky

et al. 2023

IJMS

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Survivin (BIRC5) is a tumor-associated antigen (TAA) overexpressed in various tumors but present at low to undetectable levels in normal tissue. Survivin is known to have a high expression in breast cancer (e.g., Ductal Carcinoma in situ (DCIS) and triple negative breast cancer). Previous studies have not compared survivin expression levels in DCIS tumor samples to levels in adjacent, normal breast tissue from the same patient. To ensure the effective use of survivin as a target for T cell immunotherapy of breast cancer, it is essential to ascertain the varying levels of survivin expression between DCIS tumor tissue samples and the adjacent normal breast tissue taken from the same patient simultaneously. Next-generation sequencing of RNA (RNA-seq) in normal breast tissue and tumor breast tissue from five women presenting with DCIS for lumpectomy was used to identify sequence variation and expression levels of survivin. The identity of both tumor and adjacent normal tissue samples were corroborated by histopathology. Survivin was overexpressed in human breast tissue tumor samples relative to the corresponding adjacent human normal breast tissue. Wild-type survivin transcripts were the predominant species identified in all tumor tissue sequenced. This study demonstrates upregulated expression of wild type survivin in DCIS tumor tissue versus normal breast tissue taken from the same patient at the same time, and provides evidence that developing selective cytotoxic T lymphocyte (CTL) immunotherapy for DCIS targeting survivin warrants further study.

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Section: Discussionmentioning

confidence: 99%

Survivin Expression in Luminal Breast Cancer and Adjacent Normal Tissue for Immuno-Oncology Applications

Wright,

Burkholz,

Zelinsky

et al. 2023

IJMS

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show abstract

“…To date, studies on the use of immunotherapy in ovarian carcinoma have not achieved the expected results [4,[7][8][9]. However, in the American Society of Clinical Oncology (ASCO) Congress of 2023, the results of a multicenter study were presented that observed that patients treated with chemotherapy, bevacizumab, and durvalumab and with maintenance therapy of bevacizumab, durvalumab, and olaparib showed longer disease-free survival than patients with standard treatment, regardless of the mutational state of the BRCA gene [34].…”

Section: The Predictive Role Of Tils Especially Ietils and The Potent...mentioning

confidence: 99%

“…There is a demonstrated relationship between TILs and the response to immunotherapy, such that in most neoplasms the tumors with a greater quantity of TILs have a better response [9][10][11]35]. The low success of immunotherapy in ovarian cancer has made TILs a seldom relevant parameter, although the observance of poorer response to treatment of HG-SOC with a relatively low quantity of TILs suggests a certain role for the immune infiltrate in antitumor resistance [36].…”

Section: The Predictive Role Of Tils Especially Ietils and The Potent...mentioning

confidence: 99%

“…Immunotherapy trials on ovarian carcinoma have yielded contradictory results, although a significant benefit has been observed in certain patient groups [2,7,8]. There is, therefore, a need to identify new response prediction biomarkers that allow for the proper selection of patients [3,8,9]. Studies have described the important role played by the tumor microenvironment in the response to immunotherapy, focusing mainly on the study of tumor-infiltrating lymphocytes (TILs) and various markers such as programmed death ligand 1 (PD-L1) [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

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Machine Learning Quantification of Intraepithelial Tumor-Infiltrating Lymphocytes as a Significant Prognostic Factor in High-Grade Serous Ovarian Carcinomas

Machuca-Aguado,

Conde-Martín,

Alvarez-Muñoz

et al. 2023

IJMS

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The prognostic and predictive role of tumor-infiltrating lymphocytes (TILs) has been demonstrated in various neoplasms. The few publications that have addressed this topic in high-grade serous ovarian carcinoma (HGSOC) have approached TIL quantification from a semiquantitative standpoint. Clinical correlation studies, therefore, need to be conducted based on more accurate TIL quantification. We created a machine learning system based on H&E-stained sections using 76 molecularly and clinically well-characterized advanced HGSOC. This system enabled immune cell classification. These immune parameters were subsequently correlated with overall survival (OS) and progression-free survival (PFI). An intense colonization of the tumor cords by TILs was associated with a better prognosis. Moreover, the multivariate analysis showed that the intraephitelial (ie) TILs concentration was an independent and favorable prognostic factor both for OS (p = 0.02) and PFI (p = 0.001). A synergistic effect between complete surgical cytoreduction and high levels of ieTILs was evidenced, both in terms of OS (p = 0.0005) and PFI (p = 0.0008). We consider that digital analysis with machine learning provided a more accurate TIL quantification in HGSOC. It has been demonstrated that ieTILs quantification in H&E-stained slides is an independent prognostic parameter. It is possible that intraepithelial TIL quantification could help identify candidate patients for immunotherapy.

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Predictive biomarkers of response to immunotherapy in triple-negative breast cancer – state of the art and future perspectives

Cited by 2 publications

References 0 publications

Survivin Expression in Luminal Breast Cancer and Adjacent Normal Tissue for Immuno-Oncology Applications

Survivin Expression in Luminal Breast Cancer and Adjacent Normal Tissue for Immuno-Oncology Applications

Machine Learning Quantification of Intraepithelial Tumor-Infiltrating Lymphocytes as a Significant Prognostic Factor in High-Grade Serous Ovarian Carcinomas

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