The adequacy of tissue microarrays in the assessment of inter- and intra-tumoural heterogeneity of infiltrating lymphocyte burden in leiomyosarcoma

Lee, A. T. J.; Chew, Winston; Wilding, Christopher P; Guljar, Nafia; Smith, Myles; Strauß, D.; Fisher, Charles; Hayes, Andrew; Judson, Ian; Thway, Khin; Jones, Robin L.; Huang, Paul H.

doi:10.1038/s41598-019-50888-5

Cited by 25 publications

(19 citation statements)

References 41 publications

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“…Previous studies involved TILs and its subtypes also correlated with survival in soft tissue sarcoma [ 39 – 41 ]. A study involved 47 leiomyosarcomas revealed an average number of 10.5 CD4+ TILs and 16.1 CD8+ TILs per high power filed (CD4 33.87/mm 2 , CD8 51.93/mm 2 ) [ 42 ], which is lower than the average number in MBC with mesenchymal elements (CD4 209.99 ± 140.10/mm 2 , CD8 83.34 ± 78.09/mm 2 ). Further, no significant difference in TILs was found among different mesenchymal subtypes ( p = 0.30).…”

Section: Discussionmentioning

confidence: 99%

Immune parameters associated with survival in metaplastic breast cancer

et al. 2020

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Background: Metaplastic breast carcinoma (MBC) is a rare histological type of breast cancer, which commonly shows resistance to standard therapies and is associated with poor prognosis. The immune microenvironment in MBC and its significance has not been well established due to its low incurrence rate and complex components. We aimed to investigate the diversity of immune parameters including subsets of TILs and PDL1/PD1 expression in MBC, as well as its correlation with prognosis. Methods: A total of 60 patients diagnosed with MBC from January 2006 to December 2017 were included in our study. The percentage (%) and quantification (per mm 2) of TILs and presence of tertiary lymphoid structures (TLS) were evaluated by hematoxylin and eosin staining (HE). The quantification of CD4+, CD8+ TILs (per mm 2), and PD-1/PDL1 expression were evaluated through immunohistochemistry and analyzed in relation to clinicopathological characteristics. A ≥ 1% membranous or cytoplasmatic expression of PD1 and PDL1 was considered a positive expression. Results: We found squamous cell carcinoma MBC (33/60, 55%) exhibiting most TILs of all the MBC subtypes (p = 0.043). Thirty-three of 60 (50%) of the patients had coexisting invasive ductal carcinoma of no special type (IDC-NST), and the average percentage of TILs in MBC components was lower compared with NST components (p < 0.001). Thirty (50%) patients exhibited positive (≥ 1%) PDL1 expression in their tumor cells, while 36 (60%) had positive (≥ 1%) PDL1 expression in their TILs. Twenty-seven (45%) of all the patients had positive (≥ 1%) PD1 expression in their tumor cells and 33 (55%) had PD1-positive (≥ 1%) stromal TILs. More CD8+ TILs were associated with positive PDL1 expression of tumor cells as well as positive PD1 expression in stromal cells. Greater number of stromal TILS (> 300/mm 2 , 20%), CD4+ TILs (> 250/mm 2), and CD8+ TILs (> 70/mm 2) in MBC were found associated with longer disease-free survival. Positive expression of PDL1 in tumor cells (≥ 1%) and PD1 in stromal cells (≥ 1%) were also associated with longer survival. Conclusions: The immune characteristics differ in various subtypes as well as components of MBC. Immune parameters are key predictive factors of MBC and provide the clinical significance of applying immune checkpoint therapies in patients with MBC.

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Section: Discussionmentioning

confidence: 99%

Immune parameters associated with survival in metaplastic breast cancer

et al. 2020

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“…In order to achieve comparable results and validate these markers, we suggest a standardised, international consensus for the investigation and validation of prognostic biomarkers in PDAC is developed. In line with other cancers, optimal sampling protocols for TMA analysis of PDAC are required to mitigate the effects of morphomolecular heterogeneity [83,84].…”

Section: Discussionmentioning

confidence: 99%

Immune cell infiltrates as prognostic biomarkers in pancreatic ductal adenocarcinoma: a systematic review and meta‐analysis

McGuigan

Coleman

McCain

et al. 2021

The Journal of Pathology CR

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Immune cell infiltration has been identified as a prognostic biomarker in several cancers. However, no immune based biomarker has yet been validated for use in pancreatic ductal adenocarcinoma (PDAC). We undertook a systematic review and meta‐analysis of immune cell infiltration, measured by immunohistochemistry (IHC), as a prognostic biomarker in PDAC. All other IHC prognostic biomarkers in PDAC were also summarised. MEDLINE, EMBASE and Web of Science were searched between 1998 and 2018. Studies investigating IHC biomarkers and prognosis in PDAC were included. REMARK score and Newcastle–Ottawa scale were used for qualitative analysis. Random‐effects meta‐analyses were used to pool results, where possible. Twenty‐six articles studied immune cell infiltration IHC biomarkers and PDAC prognosis. Meta‐analysis found high infiltration with CD4 (hazard ratio [HR] = 0.65, 95% confidence interval [CI] = 0.51–0.83.) and CD8 (HR = 0.68, 95% CI = 0.55–0.84.) T‐lymphocytes associated with better disease‐free survival. Reduced overall survival was associated with high CD163 (HR = 1.62, 95% CI = 1.03–2.56). Infiltration of CD3, CD20, FoxP3 and CD68 cells, and PD‐L1 expression was not prognostic. In total, 708 prognostic biomarkers were identified in 1101 studies. In summary, high CD4 and CD8 infiltration are associated with better disease‐free survival in PDAC. Increased CD163 is adversely prognostic. Despite the publication of 708 IHC prognostic biomarkers in PDAC, none has been validated for clinical use. Further research should focus on reproducibility of prognostic biomarkers in PDAC in order to achieve this.

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“…The vast majority of transcriptomic signatures in sarcoma have been developed from bulk measurements of tumour specimens. However, all the studies described to date have not systematically established if the performance of these prognostic signatures are influenced by the intratumoural heterogeneity inherent within STS 15 , 74 , for instance by evaluation of distinct heterogeneous tumour regions with spatial transcriptomics. Furthermore, there is a diversity of distinct cell types in the tumour microenvironment (e.g., immune cells, fibroblasts and endothelial cells) which can be readily assessed by histopathology review but is lost in bulk transcriptomic data.…”

Section: Outstanding Questionsmentioning

confidence: 99%

Predictive and prognostic transcriptomic biomarkers in soft tissue sarcomas

et al. 2021

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Soft tissue sarcomas (STS) are rare and heterogeneous tumours comprising over 80 different histological subtypes. Treatment options remain limited in advanced STS with high rates of recurrence following resection of localised disease. Prognostication in clinical practice relies predominantly on histological grading systems as well as sarcoma nomograms. Rapid developments in gene expression profiling technologies presented opportunities for applications in sarcoma. Molecular profiling of sarcomas has improved our understanding of the cancer biology of these rare cancers and identified potential novel therapeutic targets. In particular, transcriptomic signatures could play a role in risk classification in sarcoma to aid prognostication. Unlike other solid and haematological malignancies, transcriptomic signatures have not yet reached routine clinical use in sarcomas. Herein, we evaluate early developments in gene expression profiling in sarcomas that laid the foundations for transcriptomic signature development. We discuss the development and clinical evaluation of key transcriptomic biomarker signatures in sarcomas, including Complexity INdex in SARComas (CINSARC), Genomic Grade Index, and hypoxia-associated signatures. Prospective validation of these transcriptomic signatures is required, and prospective trials are in progress to evaluate reliability for clinical application. We anticipate that integration of these gene expression signatures alongside existing prognosticators and other Omics methodologies, including proteomics and DNA methylation analysis, could improve the identification of ‘high-risk’ patients who would benefit from more aggressive or selective treatment strategies. Moving forward, the incorporation of these transcriptomic prognostication signatures in clinical practice will undoubtedly advance precision medicine in the routine clinical management of sarcoma patients.

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The adequacy of tissue microarrays in the assessment of inter- and intra-tumoural heterogeneity of infiltrating lymphocyte burden in leiomyosarcoma

Cited by 25 publications

References 41 publications

Immune parameters associated with survival in metaplastic breast cancer

Immune parameters associated with survival in metaplastic breast cancer

Immune cell infiltrates as prognostic biomarkers in pancreatic ductal adenocarcinoma: a systematic review and meta‐analysis

Predictive and prognostic transcriptomic biomarkers in soft tissue sarcomas

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