Mutation burden as a biomarker of response to immune checkpoint therapy in nine solid cancers.

2017 ◽  
Vol 35 (7_suppl) ◽  
pp. 35-35 ◽  
Author(s):  
Shridar Ganesan ◽  
Gyan Bhanot ◽  
Janice M. Mehnert ◽  
Ann W. Silk ◽  
Jeffrey S. Ross ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
T Cells ◽  
Immune Checkpoint ◽  
Solid Cancer ◽  
Cancer Type ◽  
Her2 Breast Cancer ◽  
Mutation Burden ◽  
Gene Expression Signatures ◽  
Cancer Types

35 Background: A high mutation burden a biomarker of response to immune checkpoint therapy in melanoma, non-small cell lung cancer, and colorectal cancer. It is unknown whether mutation burden is predictive of response in other cancer types, and whether it is identifiable using available clinical assays. Methods: Using data for 10,745 tumors from 33 solid cancer types in TCGA, we looked for a mutation burden threshold (iCAM) in each cancer type associated with gene expression signatures of a blocked immune response of robust CD8+T cell response and up-regulation of immune checkpoint genes. Results: A unique iCAM threshold was identified in nine cancers: melanoma and lung, colon, endometrial, and gastric adenocarcinoma; serous ovarian, bladder urothelial, cervical, and ER+ HER2− breast cancer. iCAM thresholds applied to published clinical data for patients treated with immune checkpoint therapy showed that iCAM+ patients had significantly better response. iCAM+ tumors can be identified from clinical-grade NGS assays with high accuracy . In a prospective melanoma cohort of patients treated with anti- PD-1 patients with iCAM+ tumors had significantly better objective response rates, progression free survival, and overall survival compared patients to iCAM− tumors. Pattern of somatic mutations were different in iCAM+ and iCAM− tumors, suggesting different mechanism of carcinogenesis in iCAM+ versus iCAM− tumors. Higher fractions of leukocytes were NK (Natural Killer) cells and macrophages were M1 polarized, and a lower fraction of T cells were regulatory T cells in iCAM+ tumors compared to iCAM− tumors. Over 75% of the genes significantly up-regulated in iCAM+ tumors in every cancer types were in the immune response pathway, confirming immune response to be the main differentiator in iCAM+ veruss iCAM− tumors. Conclusions: In nine cancer types, a clinically useful mutation burden threshold (iCAM) associated with gene expression signatures of blocked immune response can identify likely responders to immune checkpoint therapy, and iCAM status is identifiable using currently available clinical NGS assays.

scholarly journals Gene Expression Signatures Based on Variability can Robustly Predict Tumor Progression and Prognosis

2015 ◽  
Vol 14 ◽  
pp. CIN.S23862 ◽  
Author(s):  
Wikum Dinalankara ◽  
Héctor Corrada Bravo
Keyword(s):  
Gene Expression ◽  
Normal Tissue ◽  
Tissue Expression ◽  
Cancer Prognosis ◽  
Clinical Settings ◽  
Cancer Type ◽  
Genomic Signatures ◽  
Normal Expression ◽  
Gene Expression Signatures ◽  
Cancer Types

Gene expression signatures are commonly used to create cancer prognosis and diagnosis methods, yet only a small number of them are successfully deployed in the clinic since many fail to replicate performance on subsequent validation. A primary reason for this lack of reproducibility is the fact that these signatures attempt to model the highly variable and unstable genomic behavior of cancer. Our group recently introduced gene expression anti-profiles as a robust methodology to derive gene expression signatures based on the observation that while gene expression measurements are highly heterogeneous across tumors of a specific cancer type relative to the normal tissue, their degree of deviation from normal tissue expression in specific genes involved in tissue differentiation is a stable tumor mark that is reproducible across experiments and cancer types. Here we show that constructing gene expression signatures based on variability and the anti-profile approach yields classifiers capable of successfully distinguishing benign growths from cancerous growths based on deviation from normal expression. We then show that this same approach generates stable and reproducible signatures that predict probability of relapse and survival based on tumor gene expression. These results suggest that using the anti-profile framework for the discovery of genomic signatures is an avenue leading to the development of reproducible signatures suitable for adoption in clinical settings.

Pan-cancer opportunities for off-label immunotherapy based on nonsynonymous mutation burden.

2017 ◽  
Vol 35 (7_suppl) ◽  
pp. 14-14
Author(s):  
Todd Cory Knepper ◽  
Jamie K. Teer ◽  
Christine Marie Walko ◽  
Howard L. McLeod
Keyword(s):  
Clinical Benefit ◽  
Solid Cancer ◽  
Cancer Type ◽  
Synonymous Mutation ◽  
Nonsynonymous Mutation ◽  
Off Label ◽  
Action Committee ◽  
Mutation Burden ◽  
Cancer Types

14 Background: In an effort to better predict which cancer patients (pts) are more likely to derive clinical benefit from immunotherapy, an association between increased non-synonymous mutation burden and likelihood of clinical response has been described. This study reports the mutation burden of pts with a variety of advanced cancers within a real-world clinical genomics database in order to highlight opportunities where off-label immunotherapy can be considered. Methods: For each solid cancer assayed by FoundationOne within Moffitt’s Clinical Genomic Action Committee (CGAC) database, a non-synonymous mutation burden was determined. Pts were then grouped by cancer type and descriptive statistics used to describe the mutation burden. For cancers with at least 5 cases, the percentage of pts with a non-synonymous mutation burden exceeding a threshold shown to be suggestive of clinical benefit from immunotherapy ( ≥ 13) is reported. The threshold was derived via linear regression from the “intermediate-high” mutation burden classification of the FoundationOne assay. Results: 520 pts received a FoundationOne test. The median non-synonymous mutation burden was 7 and the mean was 11.4. More pts with cancers that have demonstrated response to immunotherapy had a mutation burden exceeding the threshold (19.7% for lung – 45.0% for melanoma). Pt tumors from cancer types without immunotherapy indications sometimes (5.0% for salivary gland – 10.5% for breast and colorectal cancer) exceeded mutation threshold suggestive of benefit. Conclusions: A meaningful proportion of pts with cancer types without FDA-approved immunotherapies have a mutation burden for which immunotherapy may represent a clinical consideration. [Table: see text]

scholarly journals The Price of Success: Immune-Related Adverse Events from Immunotherapy in Lung Cancer

2021 ◽  
Vol 28 (6) ◽  
pp. 4392-4407
Author(s):  
Courtney H. Coschi ◽  
Rosalyn A. Juergens
Keyword(s):  
Immune Response ◽  
Adverse Events ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Low Grade ◽  
Cancer Type ◽  
Immune System Activation ◽  
Cancer Types ◽  
System Activation

Cancer immunotherapy has the goal of enhancing a patient’s intrinsic immune processes in order to mount a successful immune response against tumor cells. Cancer cells actively employ tactics to evade, delay, alter, or attenuate the anti-tumor immune response. Immune checkpoint inhibitors (ICIs) modulate endogenous regulatory immune mechanisms to enhance immune system activation, and have become the mainstay of therapy in many cancer types. This activation occurs broadly and as a result, activation is supraphysiologic and relatively non-specific, which can lead to immune-related adverse events (irAEs), the frequency of which depends on the patient, the cancer type, and the specific ICI antibody. Careful assessment of patients for irAEs through history taking, physical exam, and routine laboratory assessments are key to identifying irAEs at early stages, when they can potentially be managed more easily and before progressing to higher grades or more serious effects. Generally, most patients with low grade irAEs are eligible for re-challenge with ICIs, and the use of corticosteroids to address an irAE is not associated with poorer patient outcomes. This paper reviews immune checkpoint inhibitors (ICIs) including their mechanisms of action, usage, associated irAEs, and their management.

scholarly journals Genomic and Immunologic Correlates of Indoleamine 2,3-Dioxygenase Pathway Expression in Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Anshuman Panda ◽  
Shridar Ganesan
Keyword(s):  
Clinical Trials ◽  
Phase Iii ◽  
Cancer Type ◽  
Over Expression ◽  
Indoleamine 2,3 Dioxygenase ◽  
Her2 Breast Cancer ◽  
Specific Subset ◽  
Pathway Expression ◽  
Mutation Burden ◽  
Cancer Types

Immune checkpoint blockade leads to unprecedented responses in many cancer types. An alternative method of unleashing anti-tumor immune response is to target immunosuppressive metabolic pathways like the indoleamine 2,3-dioxygenase (IDO) pathway. Despite promising results in Phase I/II clinical trials, an IDO-1 inhibitor did not show clinical benefit in a Phase III clinical trial. Since, a treatment can be quite effective in a specific subset without being effective in the whole cancer type, it is important to identify the subsets of cancers that may benefit from IDO-1 inhibitors. In this study, we looked for the genomic and immunologic correlates of IDO pathway expression in cancer using the Cancer Genome Atlas (TCGA) dataset. Strong CD8+ T-cell infiltration, high mutation burden, and expression of exogenous viruses [Epstein-Barr virus (EBV), Human papilloma virus (HPV), and Hepatitis C virus (HCV)] or endogenous retrovirus (ERV3-2) were associated with over-expression of IDO-1 in most cancer types, IDO-2 in many cancer types, and TDO-2 in a few cancer types. High mutation burden in ER+ HER2− breast cancer, and ERV3-2 expression in ER− HER2− and HER2+ breast, colon, and endometrial cancers were associated with over-expression of all three genes. These results may have important implications for guiding development clinical trials of IDO-1 inhibitors.

scholarly journals Estimating the predictive power of silent mutations on cancer classification and prognosis

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Tal Gutman ◽  
Guy Goren ◽  
Omri Efroni ◽  
Tamir Tuller
Keyword(s):  
Gene Expression ◽  
Predictive Power ◽  
Predictive Ability ◽  
Cancer Classification ◽  
Silent Mutation ◽  
Cancer Type ◽  
Coding Region ◽  
Probability Of Survival ◽  
Diagnosis And Prognosis ◽  
Cancer Types

AbstractIn recent years it has been shown that silent mutations, in and out of the coding region, can affect gene expression and may be related to tumorigenesis and cancer cell fitness. However, the predictive ability of these mutations for cancer type diagnosis and prognosis has not been evaluated yet. In the current study, based on the analysis of 9,915 cancer genomes and approximately three million mutations, we provide a comprehensive quantitative evaluation of the predictive power of various types of silent and non-silent mutations over cancer classification and prognosis. The results indicate that silent-mutation models outperform the equivalent null models in classifying all examined cancer types and in estimating the probability of survival 10 years after the initial diagnosis. Additionally, combining both non-silent and silent mutations achieved the best classification results for 68% of the cancer types and the best survival estimation results for up to nine years after the diagnosis. Thus, silent mutations hold considerable predictive power over both cancer classification and prognosis, most likely due to their effect on gene expression. It is highly advised that silent mutations are integrated in cancer research in order to unravel the full genomic landscape of cancer and its ramifications on cancer fitness.

scholarly journals Cancer-Specific Immune Prognostic Signature in Solid Tumors and Its Relation to Immune Checkpoint Therapies

Cancers ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2476 ◽  
Author(s):  
Shaoli Das ◽  
Kevin Camphausen ◽  
Uma Shankavaram
Keyword(s):  
Immune Function ◽  
Solid Tumors ◽  
Immune Checkpoint ◽  
Data Sets ◽  
Cancer Type ◽  
Rna Seq ◽  
Prognostic Signature ◽  
Cell Functions ◽  
Cancer Types ◽  
Disease Free

To elucidate the role of immune cell infiltration as a prognostic signature in solid tumors, we analyzed immune-function-related genes from four publicly available single-cell RNA-Seq data sets and twenty bulk tumor RNA-Seq data sets from The Cancer Genome Atlas (TCGA). Unsupervised clustering of pan-cancer transcriptomic signature showed two major immune function types: one related to NK-, T-, and B-cell functions and the other related to monocyte, macrophage, dendritic cell, and Toll-like receptor functions. Kaplan–Meier analysis showed differential prognosis of these two groups, dependent on the cancer type. Our analysis of TCGA solid tumors with an elastic net model identified 155 genes associated with disease-free survival in different tumor types with varied influence across different cancer types. With this gene set, we computed cancer-specific prognostic immune score models for individual cancer types that predicted disease-free and overall survival. Validation of our model on available published data of immune checkpoint blockade therapies on melanoma, kidney renal cell carcinoma, non-small cell lung cancer, gastric cancer and bladder cancer confirmed that cancer-specific higher immune scores are associated with response to immunotherapy. Our analysis provides a comprehensive map of cancer-specific immune-related prognostic gene sets that are associated with immunotherapy response.

scholarly journals The JAK1/2 Inhibitor Ruxolitinib Downregulates the Immune Checkpoint Protein B7-H3 in Multiple Myeloma

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 1824-1824
Author(s):  
Ning Xu ◽  
Nicole Ng ◽  
Mingjie Li ◽  
Erin Yu ◽  
Eric Sanchez ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Immune Checkpoint ◽  
Research Funding ◽  
Flow Cytometric Analysis ◽  
Cell Activity ◽  
Cytokine Signaling ◽  
Checkpoint Protein ◽  
Equity Ownership

Introduction: The JAKSTAT pathway plays a critical role in the regulation of hematopoietic pathways and immunological cytokine signaling. The JAK pathway is also involved in tumor cell proliferation and drug resistance in multiple myeloma (MM). Thus, inhibition of the JAK pathway should be a potentially effective strategy for treating MM patients. B7-H3 is an immune checkpoint protein in the B7 superfamily and has been shown overexpressed in several tumors. Immune checkpoint blockade may suppress tumor progression or enhance anti-tumor immune responses. In this study, we investigated the effects of the JAK1/2 inhibitor ruxolitinib (Rux) on B7-H3 in MM. Materials and Methods: Bone marrow mononuclear cells (BMMCs) were collected from MM patients after obtaining IRB approval. Single-cell suspensions were prepared from human MM LAGλ-1A xenografts which had been grown in severe combined immunodeficient mice. HS-5 stromal and SUP-T1 T cells were purchased from ATCC. The cells were cultured and treated with or without RUX and then subjected to qRT-PCR, flow cytometric analysis, and western blot analysis. For qRT-PCR, total RNA was extracted and applied to cDNA synthesis, followed by qPCR. Gene expression was analyzed in MM BMMCs alone or co-cultured with stromal cells or T cells with or without Rux treatment (1μM) in vitro. Results: We identified increased B7-H3 expression in MMBMMCs from patients with progressive disease (PD) patients compared to those in complete remission (CR). Rux significantly reduced B7-H3 expression in MMBMMCs in patients with PD, MM cells (U266), and BM from patients in PD when co-cultured with stromal cells (HS-5) after 48-72 hours. Rux decreased B7H3 expression in the human MM xenograft model LAGλ-1A when cultured ex vivo. In addition, Rux suppressed B7-H3 at protein levels as shown with flow cytometric analysis and western blotting, consistent with the gene expression results. Next, we tested whether B7-H3 blockade by Rux could potentially restore exhausted T cell activity against myeloma cells in MMBM. We found that Rux can increase IL-2 and CD8 gene expression in MMBM with lower plasma percentages (< 30%) but not among those with higher plasma cell percentages (>70%). Rux also elevated IL-2 and CD8 gene expression in BM when it was cocultured with T cells (SUP-T1), suggesting Rux may mediate immunological cytokine signaling. B7-H3-neutralizing antibody increased CD8 gene expression in MMBM in vitro, suggesting that one of the mechanisms through which Rux upregulates CD8 T cells in MMBM may be via downregulation of B7-H3. Conclusion: The immune checkpoint protein B7-H3 is overexpressed in MMBM in PD compared to CR patients. The JAK1/2 inhibitor Rux can decrease B7-H3 expression and increase IL-2 and CD8 expression in BM in vitro. Our results provide evidence for Rux inhibiting the immune checkpoint protein B7-H3 which may potentially restore exhausted T-cell activity in the MMBM tumoral microenvironment. Disclosures Chen: Oncotraker Inc: Equity Ownership. Berenson:Amgen: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Sanofi: Consultancy; Sanofi: Consultancy; Amag: Consultancy, Speakers Bureau; Amag: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; OncoTracker: Equity Ownership, Other: Officer; OncoTracker: Equity Ownership, Other: Officer; Bristol-Myers Squibb: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Incyte Corporation.: Consultancy, Research Funding; Incyte Corporation.: Consultancy, Research Funding; Takeda: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau.

scholarly journals Early Response of CD8+ T Cells in COVID-19 Patients

2021 ◽  
Vol 11 (12) ◽  
pp. 1291
Author(s):  
Deni Ramljak ◽  
Martina Vukoja ◽  
Marina Curlin ◽  
Katarina Vukojevic ◽  
Maja Barbaric ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
T Cells ◽  
Mrna Expression ◽  
Cd8 T Cells ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Effector Memory ◽  
Healthy Controls ◽  
Ifn Γ

Healthy and controlled immune response in COVID-19 is crucial for mild forms of the disease. Although CD8+ T cells play important role in this response, there is still a lack of studies showing the gene expression profiles in those cells at the beginning of the disease as potential predictors of more severe forms after the first week. We investigated a proportion of different subpopulations of CD8+ T cells and their gene expression patterns for cytotoxic proteins (perforin-1 (PRF1), granulysin (GNLY), granzyme B (GZMB), granzyme A (GZMA), granzyme K (GZMK)), cytokine interferon-γ (IFN-γ), and apoptotic protein Fas ligand (FASL) in CD8+ T cells from peripheral blood in first weeks of SARS-CoV-2 infection. Sixteen COVID-19 patients and nine healthy controls were included. The absolute counts of total lymphocytes (p = 0.007), CD3+ (p = 0.05), and CD8+ T cells (p = 0.01) in COVID-19 patients were significantly decreased compared to healthy controls. In COVID-19 patients in CD8+ T cell compartment, we observed lower frequency effector memory 1 (EM1) (p = 0.06) and effector memory 4 (EM4) (p < 0.001) CD8+ T cells. Higher mRNA expression of PRF1 (p = 0.05) and lower mRNA expression of FASL (p = 0.05) at the fifth day of the disease were found in COVID-19 patients compared to healthy controls. mRNA expression of PRF1 (p < 0.001) and IFN-γ (p < 0.001) was significantly downregulated in the first week of disease in COVID-19 patients who progressed to moderate and severe forms after the first week, compared to patients with mild symptoms during the entire disease course. GZMK (p < 0.01) and FASL (p < 0.01) mRNA expression was downregulated in all COVID-19 patients compared to healthy controls. Our results can lead to a better understanding of the inappropriate immune response of CD8+ T cells in SARS-CoV2 with the faster progression of the disease.

scholarly journals PD-L1 Checkpoint Blockade Augments Anti-Tumor Immune Response of GD2 or HER2-Bsab Ex Vivo Armed T-Cells (EVAT) Therapy in Osteosarcoma

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 1959-1959
Author(s):  
Jeong A Park ◽  
Hong fen Guo ◽  
Hong Xu ◽  
Nai-Kong V. Cheung
Keyword(s):  
Immune Response ◽  
T Cells ◽  
T Cell ◽  
Immune Checkpoint ◽  
Bispecific Antibody ◽  
Ex Vivo ◽  
Activated T Cells ◽  
The Impact ◽  
Anti Tumor Activity

Background Ex Vivo Armed T-cells (EVAT) carrying zeptomoles (10-21M) of T-cell engaging GD2-bispecific antibody (GD2-EVAT) or HER2-bispecific antibodies (HER2-EVAT) have potent anti-tumor activity against GD2(+) and/or HER2(+) solid tumors. Strategies to further optimize this approach are highly relevant. PD-1 is a key immune checkpoint receptor expressed mainly by activated T-cells and mediates immune suppression by binding to its ligands PD-L1 or PD-L2. Upregulation of PD-L1 has been found in many cancers including osteosarcoma and associated with aggressive disease and poor outcome. While the use of immune checkpoint inhibitors (ICIs) seems logical, the ideal timing when combined with T-cell engaging bispecific antibody (T-BsAb) or EVAT has yet to be defined. Here, we described the effects of anti-PD-1 or anti-PD-L1 antibodies on GD2-EVAT or HER2-EVAT therapy and explored the impact of its timing in the treatment of osteosarcoma which is GD2(+), HER2(+) and PD-L1(+). Methods GD2-BsAb and HER-BsAb were built using the IgG(L)-scFv format (Can Immunol Res, 3:266, 2015, Oncoimmunology, PMID:28405494). T-cells from healthy volunteer donors were isolated, and cultured ex vivo in the presence of CD3/CD28 beads plus 30 IU/mL of interleukin 2 (IL-2). Between day 7 and day 14, activated T-cells (ATCs) were harvested and armed for 20 minutes at room temperature with GD2-BsAb or HER2-BsAb. In vivo anti-tumor activity against GD2(+), HER2(+), and PD-L1(+) osteosarcoma cell line xenografts was tested in BALB-Rag2-/-IL-2R-γc-KO mice. Anti-human PD-1 antibody (pembrolizumab, anti-PD-1) or anti-human PD-L1 antibody (atezolizumab, anti-PD-L1) were tested for synergy with GD2-EVAT or HER2-EVAT therapy. Results The PD-1 expression increased among T-cells that circulated in the blood, that infiltrated the spleen or the tumor after EVAT therapy. While anti-PD-L1 combination therapy with GD2-EVAT or HER2-EVAT improved anti-tumor response against osteosarcoma (P=0.0123 and P=0.0004), anti-PD-1 did not (all P>0.05). The addition of anti-PD-L1 significantly increased T-cell survival in blood and T-cell infiltration of tumor when compared to GD2-EVAT or HER2-EVAT alone (all P<0.0001). Treatment of GD2-EVAT or anti-PD-L1 plus GD2-EVAT downregulated GD2 expression on tumors, but anti-PD-1 plus GD2-EVAT did not. For the next step we tested the impact of different combination schedules of ICIs on GD2-EVAT therapy. Concurrent anti-PD-1 (6 doses along with GD2-EVAT therapy) interfered with GD2-EVAT, while sequential anti-PD-1 (6 doses after GD2-EVAT) did not make a significant effect (P>0.05). On the other hand, while the concurrent use of anti-PD-L1 did not show benefit on GD2-EVAT, sequentially administered anti-PD-L1 produced a significant improvement in tumor control when compared to anti-PD-L1 or GD2-EVAT alone (P=0.002 and P=0.018). When anti-PD-L1 treatment was extended (12 doses after GD2-EVAT), the anti-tumor effect was most pronounced compared to GD2-EVAT alone (P <0.0001), which translated into improved survival (P=0.0057). These in vivo anti-tumor responses were associated with increased CD8(+) tumor infiltrating lymphocytes (TILs) of tumor. Conclusion In the arming platform, large numbers of target-specific T-cells can be generated, and this EVAT therapy is a highly effective cellular treatment with high potency in preclinical models. In addition, the advantage of ex vivo cytokine release following T-cell arming and activation could reduce or avoid life threatening cytokine storm if such activation was to proceed in vivo. Adoptive T-cell therapy induced immune response upregulates the inhibitory immune checkpoint PD-1/PD-L1 pathway, and combination treatment with anti-PD-L1 antibody, especially when combined as sequential therapy and continuously treated, significantly improved anti-tumor effect of EVAT, partly through increase in CD8(+) TILs infiltration. Disclosures Xu: MSK: Other: co-inventors in patents on GD2 bispecific antibody and HER2 bispecific antibody. Cheung:Ymabs: Patents & Royalties, Research Funding.

scholarly journals Analyzing cancer gene expression data through the lens of normal tissue-specificity

2021 ◽  
Author(s):  
H. Robert Frost
Keyword(s):  
Gene Expression ◽  
Normal Tissue ◽  
Tissue Specificity ◽  
Cancer Genomics ◽  
Expression Profiles ◽  
Genetic Alterations ◽  
Cancer Type ◽  
Tissue Specific ◽  
Normal Tissues ◽  
Cancer Types

AbstractThe genetic alterations that underlie cancer development are highly tissue-specific with the majority of driving alterations occurring in only a few cancer types and with alterations common to multiple cancer types often showing a tissue-specific functional impact. This tissue-specificity means that the biology of normal tissues carries important information regarding the pathophysiology of the associated cancers, information that can be leveraged to improve the power and accuracy of cancer genomic analyses. Research exploring the use of normal tissue data for the analysis of cancer genomics has primarily focused on the paired analysis of tumor and adjacent normal samples. Efforts to leverage the general characteristics of normal tissue for cancer analysis has received less attention with most investigations focusing on understanding the tissue-specific factors that lead to individual genomic alterations or dysregulated pathways within a single cancer type. To address this gap and support scenarios where adjacent normal tissue samples are not available, we explored the genome-wide association between the transcriptomes of 21 solid human cancers and their associated normal tissues as profiled in healthy individuals. While the average gene expression profiles of normal and cancerous tissue may appear distinct, with normal tissues more similar to other normal tissues than to the associated cancer types, when transformed into relative expression values, i.e., the ratio of expression in one tissue or cancer relative to the mean in other tissues or cancers, the close association between gene activity in normal tissues and related cancers is revealed. As we demonstrate through an analysis of tumor data from The Cancer Genome Atlas and normal tissue data from the Human Protein Atlas, this association between tissue-specific and cancer-specific expression values can be leveraged to improve the prognostic modeling of cancer, the comparative analysis of different cancer types, and the analysis of cancer and normal tissue pairs.

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