(CTN News) – Stanford Medicine examined thousands of breast cancer tumors and found that fetal DNA patterns predict cancer kind and severity decades later.
The findings challenge the concept that random mutations cause most cancers over time. Our parents’ germline DNA may affect whether the immune system detects and removes cancer-causing mutations or lets them proliferate.
“The hereditary factors causing cancer are little understood, and most cancers are believed to be caused by random cell division errors or bad luck,” says Christina Curtis, Ph.D.
It is not true that all cancers are random. Cancer is fought by genes and immunity.
New breast cancer origins theory and tumor development indicators.”
Science study senior author Curtis. PhD postdoctoral scholar Kathleen Houlahan led the study.
It was first proposed in 2015 that some tumors are born malignant and metastatic. These findings have been confirmed by other investigators as well, but these findings shed light on how early this occurs.”
Causes of breast cancer: evolving theories.
The study may help predict and treat breast cancer by revealing immune system and cancer cell insights.
Cancer prediction uses a few gene mutations. In 1 in 500 women, BRCA1 and BRCA2 cause breast and ovarian cancer, and Li Fraumeni syndrome causes childhood and adult malignancies.
Researchers suggest tens or hundreds of healthy gene variants may eternally prevent cancer. Basically, we predict the subtypes, metastases, and aggressiveness of cancer.”
Parental genes. Type O blood, brown hair, and blue eyes can come from parents. BRCA1, BRCA2, and TP53 mutations increase newborn cancer risk. However, finding other germline changes linked to future cancers is difficult.
Most cancer genes are somatic. Tens of millions of cells divide and die daily. Mutations and mistakes can occur during DNA replication. Cancer-causing mutations are found by comparing tumor DNA to blood or tissue germline genomes.
Breast tumor classification
In 2012, Curtis studied somatic mutations in hundreds of breast cancers using machine learning. She detected 11 subtypes with different prognoses and recurrence rates, and four were more likely to return 10 or 20 years after diagnosis, helping clinicians choose treatments and discuss long-term prognoses with patients.
BRCA1 and BRCA2 mutations cause TNBC. The germline genome may change breast cancer subtypes.
“We wanted to understand how inherited DNA might sculpt how a tumor evolves,” he adds. We tested immunity.
Protein-decorated cell membranes reveal healthy breast cancer cells.
Show uses HLA mutants. T lymphocytes monitor cell-problem epitopes like fashion police. Malignant cells have abnormal proteins, while infected cells have viral proteins. These errors stimulate T-cells to kill criminals.
Oncogenes—normal genes that defy cell control—were studied by Houlahan and Curtis Genomic stuttering can make these mutations seem as DNA replicates of normal genes. Curtis initially identified breast cancer subgroups using oncogene amplifications.
Blingy T cells may prefer strong epitopes (golf-ball-sized turquoise vs. silver studs). Strong oncogenes fuel the immune system. Five vibrant turquoise earrings kill trendy T cells.
Breast tumors at various stages were studied for inherited oncogene sequence impacts on subtype. Those with a high germline epitope load (bling) and an HLA type that prominently displays that epitope were less likely to develop breast cancer subtypes that amplified that oncogene Quite surprising.
Wandering immune cells promote aggressive, poor-prognosis breast cancer.
“At the early, pre-invasive stage, a high germline epitope burden is protective against cancer,” he says. Immuno-challenged high germline epitope load tumors spread faster. Tumors shrink.”
There is basically a tug of war between tumors and immune cells, he says. There is a possibility that preinvasive cancers can be diagnosed and treated more easily. It may kill many cancers unknowingly. Sometimes immunity diminishes.
Immune escape mechanisms can develop in cancers. This finding clarifies this opaque mechanism and may lead to the development of therapeutic timings and methods for heating immunologically cold tumors for optimum effectiveness.”
In order to optimize treatment, prognosis, and recurrence surveillance for Curtis, researchers will stratify her 11 breast cancer subtypes using the germline genome.
It is used by doctors to develop cancer immunotherapies and to estimate the risk of cancer among healthy people based on blood samples.
“We began with a bold hypothesis,” Curtis said. The field had not previously considered tumor origins and evolution. This inherited, acquired, and tumor-immune co-evolution lens investigates cancer variations.”
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