Researchers from the HUN-REN Szeged Biological Research Centre and HCEMM have just published a new study suggesting that it’s not simply the number of tumour mutations that matters for immunotherapy, but the kind of mutation patterns they create. The team found a distinct “fingerprint” linked to DNA repair problems and chemical exposures that can leave tumours surprisingly hard for the immune system to spot, even when mutation counts are high. The study also points out that a patient’s genetics, including common HLA types in Europeans, can shift how visible the same tumour looks to T cells. The paper was published recently in Molecular Systems Biology.

A UCLA research team has identified the best design for a promising new type of immunotherapy that could be mass-produced to treat multiple solid tumors. The study focused on engineered invariant natural killer T cells, or NKT cells — powerful immune cells with a unique ability to infiltrate solid tumors — and systematically compared four targeting systems, called chimeric antigen receptors, or CARs, that direct these cells to attack cancer.

Scientists discovered key genetic factors that determine whether a T cell acts as a powerful disease fighter or enters an ineffective, exhausted state. Turning off two transcription factors allowed exhausted T cells to regain their ability to kill tumors. The findings could help scientists engineer more powerful T cells for cellular therapies such as adoptive cell transfer (ACT) and CAR T cell therapy.

Early cancer detection often relies on complex, invasive, and time-consuming staining procedures. A research team from Southeast University has developed a novel "label-free" biosensor that uses the physics of "band folding" to unlock high-density hidden electromagnetic modes in the sub-terahertz range. This technology creates a rich spectral fingerprint that can distinguish between normal cells and cancer cells of varying malignancy without chemical markers. By correlating macroscopic electromagnetic signals with microscopic cellular biomass density, this method offers a safe, rapid, and non-destructive path for future clinical cancer screening.

New research from Memorial Sloan Kettering Cancer Center (MSK) illuminates new details about Thetis cells that will support efforts to harness them therapeutically; shows how the timing and strength of danger signals steer immune cell fates; and employs single-nucleus DNA sequencing to shed new light on the evolution of pancreatic cancer.

Gene regulation is far more predictable than previously believed, scientists conclude after developing deep learning model PARM. This might bring an end to a scientific mystery: how genes know when to switch on or off. Today, scientists publish in Nature about their relentless back-and-forth between lab experiments and computation that enabled them to build this lightweight model. Scientists around the world can now start using this tool for reading these genetic instructions, creating leads for new cancer diagnostics, patient stratification, and future therapies.