There's a growing recognition that the molecular profile of a primary tumor can differ significantly from its metastases. To guide treatment more accurately, the preferred practice is to biopsy an accessible metastatic lesion when possible, as this better reflects the biology of the active disease being treated.

Experiments show that transferring a cancer cell's dysfunctional mitochondria—but not its nucleus—into a healthy cell is what induces cancer. This disruptive finding supports the view of cancer as a metabolic disease that can be targeted by starving its mitochondria of fuels like glucose.

Every cancer specimen is genetically unique, yet all share common traits like uncontrolled division and co-opting normal cell survival mechanisms. The key to treatment is finding pathways that are different enough from normal cells to target and exploit.

A tumor's genetic profile can evolve under treatment pressure. Retesting tissue or blood upon disease progression may reveal new, actionable mutations (e.g., in BRCA genes) that were absent at diagnosis, thereby opening up new targeted therapy options.

An individual tumor can have hundreds of unique mutations, making it impossible to predict treatment response from a single genetic marker. This molecular chaos necessitates functional tests that measure a drug's actual effect on the patient's cells to determine the best therapy.

Instead of creating therapies for hundreds of specific driver mutations, which vary widely between patients, Earli's platform targets downstream commonalities—the "hallmarks of cancer" like rapid cell proliferation. These pathways are where diverse mutations converge, creating a more universal and reliable target across different cancers.

Contrary to concerns about over-complicating treatment, experts advocate for fragmenting gastric cancer even further. The goal is to treat each molecularly defined subset as its own distinct disease, which requires deeper understanding and more targeted approaches rather than broad simplification.

Contrary to its traditional monolithic treatment approach, SCLC is now understood to have distinct transcriptomic subsets (e.g., ASCL1, NeuroD1). The future of SCLC therapy will likely involve biomarker testing to match patients with the most effective treatments for their specific subtype, mirroring the personalized approach in non-small cell lung cancer.

HER2+/ER+ breast cancer is not a single disease. Genomic subtyping reveals distinct biological profiles (luminal A/B, HER2-enriched) with pathologic complete response rates to therapy ranging from just 26% to as high as 61%, signaling the need for tailored treatment strategies.