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Publications

ASCO 24 posters
Innovation

ASCO 24 Posters

GTC presented abstracts at ASCO 2024 GTC’s posters from 2024 Convention of American Society of Clinical Oncology are now available to be downloaded. Please reach

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June 5, 2024 9:17 am
Using Targeted Transcriptome and Machine Learning of Pre- and Post-Transplant Bone Marrow Samples to Predict Acute Graft-versus-Host Disease and Overall Survival after Allogeneic Stem Cell Transplantation
Publications

Using Targeted Transcriptome and Machine Learning of Pre- and Post-Transplant Bone Marrow Samples to Predict Acute Graft-versus-Host Disease and Overall Survival after Allogeneic Stem Cell Transplantation

Acute graft-versus-host disease (aGvHD) remains a major cause of morbidity and mortality after allogeneic hematopoietic stem cell transplantation (HSCT), occurring to some degree in over 50% of patients and being a direct cause of death in about 20% of patients. This complication occurs even despite a better understanding of donor selection and GvHD prophylaxis regimens. aGvHD is a complex event in which multiple contributing factors are involved. We performed RNA transcriptome analysis of 1408 genes in bone marrow samples obtained before and after transplantation using machine learning to predict the risk of aGvHD and post-transplant survival for a cohort of patients undergoing HSCT. Differential gene expression identified several signaling pathways in the bone marrow microenvironment that may be major regulators of the complex biology of GvHD, and identified targets of intervention to ameliorate the risk of aGvHD and improve patient survival.

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April 2, 2024 9:20 am
Combining cell-free RNA with cell-free DNA in liquid biopsy forhematologic and solid tumors
Publications

Combining cell-free RNA with cell-free DNA in liquid biopsy for hematologic and solid tumors

Introducing a novel liquid biopsy approach combining cfRNA and cfDNA sequencing. Our findings demonstrate superior mutation detection with cfRNA, while cfDNA excels in identifying chromosomal aberrations. Elevated cfRNA biomarkers correlate with tumor types, aiding diagnosis. Machine learning predicts cancer types accurately. Host immune response analysis through cfRNA ratios reveals distinct patterns in cancer patients. This integrated approach holds promise for predicting genomic abnormalities and cancer diagnosis

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February 23, 2024 11:22 am
GTC - ASH 2023 posters
Innovation

ASH 23 Posters

GTC presented abstracts at ASH 2023 GTC’s posters from 2023 Convention of American Society of Hematology are now available to be downloaded. Please reach out

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December 12, 2023 10:31 am
Early cancer detection diagnostic companies have received a lot of attention and venture capital investment over the last few years with numerous labs launching diagnostic tests to address this potentially massive market. While the realized clinical value of these tests for patients is still some way off, many companies have started enrollment in clinical studies and are building databases to advance this technology. Most of these companies have focused almost exclusively on DNA methylation techniques to identify early signs of cancer. At first glance this makes sense as DNA is now a widely accepted diagnostic method for identify biological changes associated with tumor growth. However, it is perhaps an incomplete approach as the value of RNA testing and its capabilities are rapidly growing. Gene expression, which is an RNA based technique, may prove to be a more powerful tool for the purpose of early cancer detection and screening Gene expression and DNA methylation are two distinct molecular processes, with gene expression being the result of methylation. Whatever abnormalities that are found in DNA methylation should also be found in gene expression along with potentially even more clinically relevant information. Here are the key differences and considerations for each: DNA Methylation: DNA methylation is an epigenetic modification involving the addition of methyl groups to DNA molecules, typically at cytosine residues. Aberrant DNA methylation patterns are commonly associated with cancer. Pros of DNA Methylation for Early Cancer Detection: Stability: DNA methylation patterns tend to be relatively stable over time and can be detected in easily accessible samples like blood or urine. Epigenetic Insights: DNA methylation changes can reveal alterations in gene regulation and potential driver events in cancer development. Wide Applicability: DNA methylation can be used to detect various types of cancer and may have broader clinical utility. Cons of DNA Methylation for Early Cancer Detection: Limited Functional Information: DNA methylation alone does not provide direct information about the functional consequences of gene regulation changes. Heterogeneity: Methylation patterns can vary among different cancer subtypes and individuals, making interpretation complex. False Positives: Methylation changes may occur in response to factors other than cancer, leading to potential false positives. When to Use DNA Methylation: DNA methylation analysis is valuable for non-invasive or minimally invasive early cancer detection, especially when you need stability and broad applicability. It is often used in screening and diagnostic tests, such as liquid biopsies. Gene Expression: Gene expression refers to the process by which information in a gene's DNA sequence is used to produce a functional product, typically a protein. In the context of cancer detection, gene expression profiling involves measuring the levels of gene transcripts (messenger RNA or mRNA) in a cell or tissue sample. Pros of Gene Expression for Early Cancer Detection: Functional Insight: Gene expression analysis provides information about which genes are actively involved in cellular processes, potentially identifying the specific pathways dysregulated in cancer. Dynamic Information: Gene expression levels can change rapidly in response to physiological conditions or disease, making it suitable for monitoring disease progression and treatment response. High Sensitivity: It can detect subtle changes in gene expression that may be indicative of early cancer stages. Cons of Gene Expression for Early Cancer Detection: Complexity: Analyzing gene expression data has historically been technically challenging and expensive. Fragility: RNA tends to degrade faster than DNA and is more complex to work with Limited Causative Insight: While gene expression can reveal dysregulated pathways, it doesn't directly provide information about the underlying genetic mutations or epigenetic changes driving cancer. When to Use Gene Expression: Gene expression profiling is most useful when you want to gain insight into the functional changes occurring in cancer cells and when you need high sensitivity to detect early-stage cancers. It is often employed in research settings and, in some cases, for personalized treatment decisions. In closing, the choice between gene expression and DNA methylation for early cancer detection is still not clearly defined as to what will be a superior approach. Gene expression provides functional insight and high sensitivity, while DNA methylation offers stability and broader applicability. In some cases, a combination of both approaches may provide a more comprehensive understanding of cancer development and progression. GTC is currently collecting gene expression data as RNA in our opinion has several distinct advantages over DNA only approaches. Learn more about GTC’s Gene Expression capabilities for research. Time and billions of dollars will ultimately tell which of these applications are more clinically useful. We even must leave open a possibility that another approach may make sense to early cancer detection and screening. But for now, we will have to wait for more data to be collected and outcomes to be analyzed.
Publications

When it comes to early cancer detection and screening which is better? Methylation or Gene Expression 

Early cancer detection diagnostic companies have received a lot of attention and venture capital investment over the last few years with numerous labs launching diagnostic tests to address this potentially massive market. While the realized clinical value of these tests for patients is still some way off, many companies have started enrollment in clinical studies and are building databases to advance this technology. 

Read More »
October 25, 2023 9:46 am
Homologous Recombination Abnormalities
Publications

Homologous Recombination Abnormalities Associated With BRCA1/2 Mutations as Predicted by Machine Learning of Targeted Next-Generation Sequencing Data

Homologous recombination deficiency (HRD) is the hallmark of breast cancer gene 1/2 (BRCA1/2)-mutated tumors and the unique biomarker for predicting response to double-strand break (DSB)–inducing drugs. The demonstration of HRD in tumors with mutations in genes other than BRCA1/2 is considered the best biomarker of potential response to these DSB-inducer drugs.

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October 10, 2023 10:48 am
ASCO 23 posters available
Innovation

ASCO 23 Posters

GTC presented abstracts at ASCO 2023 GTC’s posters from 2023 Convention of American Society of Clinical Oncology are now available to be downloaded. Please reach

Read More »
June 8, 2023 11:12 am