LAMA3 (Laminin Subunit Alpha 3)

In this paper, we explored approaches for patient-level timeline extraction through the SACT timeline extraction task. Our results and analysis add to the knowledge of extracting treatment timelines from EMR clinical narratives using language modeling methods.

Meanwhile, soft prompting significantly enhanced the performance of smaller open LLMs. Our findings suggest that training soft prompts on smaller open models can achieve performance levels comparable to those of proprietary very large language models.

LAMA3 expression level is an independent risk factor for the occurrence of neuroinvasion in PDAC patients; LAMA3 expression level, TNM staging and prognosis of PDAC patients are correlated; LAMA3 expression level may serve as a valuable biomarker for the occurrence, development, and prediction of prognosis of patients with PDAC, and also as a potential therapeutic target for PDAC patients.

SPI1 was highly expressed in ESCC and could bind to the promoter of LAMA3 to jointly regulate the progression of ESCC. This study elucidated that SPI1 aggravated ESCC by binding to the promoter of LAMA3, thereby stimulating the growth and proliferation of ESCC cells and suppressing oxidative stress and ferroptosis.

This study demonstrates that LLMs, particularly when guided by the proposed IR strategy, can accurately and reliably perform esophageal cancer staging from free-text radiology reports. This approach not only provides high-performance predictions but also offers a transparent and verifiable reasoning process, highlighting its potential as a valuable decision-support tool to augment human expertise in complex clinical diagnostic tasks.

This study demonstrates that context-aware LLM prompts substantially improved the efficiency and effectiveness of classifying TRCs from radiology reports, despite potential intrinsic hallucinations. While further improvements are required for real-world application, our findings suggest that context-aware prompts have significant potential for segmenting complex radiology reports and enhancing oncology clinical workflows.

A state-of-the-art medical LLM can answer real-life questions from the clinical practice of radiation oncology similarly well as clinical experts regarding overall quality and potential harmfulness. Such LLMs can already be deployed within the local hospital environment at an affordable cost. While LLMs may not yet be ready for clinical implementation as general AI assistants, the technology continues to improve at a rapid pace. Evaluation studies based on real-life situations are important to better understand the weaknesses and limitations of LLMs in clinical practice. Such studies are also crucial to define when the technology is ready for clinical implementation. Furthermore, education for health care professionals on generative AI is needed to ensure responsible clinical implementation of this transforming technology.

In conclusion, HEYL activates the transcription of LAMA3, which in turn reduces EC radiosensitivity via the EMT pathway.

This study unveils new somatic alterations in different genes among early-onset Pakistani breast cancer patients, offering valuable insights for drug design targeting breast carcinoma.

An atlas of TAMs was constructed in PC. SPP1 + macrophages drove pancreatic cancer progression via ITGB6-mediated interactions.

Based on a detailed analysis of their performance metrics in a zero-shot setting, we developed two instruction-tuned models: Path-llama3.1-8B and Path-GPT-4o-mini-FT. These models demonstrated superior performance in zero-shot cancer type identification, staging, and prognosis assessment compared to the other models evaluated.

Knockdown of LAMA3 suppressed cell proliferation by 57% (p < 0.001), migration by 49% (p < 0.001), and invasion by 47% (p < 0.001).Pathway enrichment analysis indicated involvement of LAMA3 and its co-expressed genes in cell adhesion, extracellular matrix organization, and the PI3K-AKT pathway. In summary, our results demonstrate that LAMA3 is a major promoter of ESCC progression and a potential biomarker and therapeutic target.