Based on the provided sources, there are several biomarkers for non-small cell lung cancer (NSCLC) that are currently gaining attention in preliminary research but haven't been widely acknowledged or utilized in the broader biomedical field.

1. MicroRNAs (miRNAs): miRNAs are short non-coding RNA molecules that function as key regulators in various biological processes. Their dysregulation results in many diseases including cancer and autoimmune disorders (Liu et al., 2018 (SOURCE1)). Specifically, microRNA-148a has been found to target Bcl-2 in patients with NSCLC (Wang et al., 2019 (SOURCE1)).

2. Long non-coding RNAs (lncRNAs): lncRNAs have been identified as promising biomarkers and potential therapeutic targets for NSCLC. For example, PANDAR and LncRNA RP11 713B9.1 have been described as such (Zhao Tianying, Khadka Vedbar Singh and Deng Youping, 2020 (SOURCE2)).

It's worth noting that while these biomarkers show promise, they have not yet been widely acknowledged or utilized in the broader biomedical field, and further research is needed to confirm their clinical utility.

Based on the provided sources, there are a few under-reported findings or trends from oncology clinical trials that the wider healthcare community should consider focusing on more.

1. Personalized Medicine and Biomarkers: There is a shift towards hypothesis-driven and biomarker-based studies in oncology clinical trials, setting the stage for precision medicine (SOURCE6). This includes the study of new biomarkers and biological drivers of cancer to set the possibility of new therapeutic opportunities (SOURCE6). Additionally, pharmacogenetic biomarkers have undergone an exponential increase in FDA drug labels over the last decade (SOURCE5).

2. Limited Sample Size in Oncology Trials: Many oncology clinical trials involve small samples due to specific eligibility criteria, which can lead to reliance on studies with limited data to inform clinical and economic assessments of new therapies (SOURCE3).

3. Drug Repurposing: This strategy for identifying new therapeutic indications for approved or investigational drugs that are outside the scope of the original development could be a more cost-effective and time-efficient approach for cancer drug development (SOURCE7).

Real-time, continuous data monitoring through wearable technology has the potential to significantly contribute to the early identification and management of cardiovascular diseases (CVDs) based on the provided sources.

1. Wearables' potential in CVD detection: Wearable devices can provide continuous, long-term, and real-time monitoring of health data, such as heart rate, which can help identify potential health problems related to CVDs (SOURCE3).

2. Complementary monitoring: PPG and ECG sensors in wearables can monitor various physiological parameters relevant to cardiac health, providing enriched data when combined (SOURCE5).

3. Bridging the gap: Monitoring technologies from a technological standpoint and the clinical standpoint of CVDs need to be linked to establish a clear understanding and bridge the gap between the two (SOURCE5).

4. Automated actions: The integration of wearables and other IoT devices in monitoring CVDs holds significant promise, but widespread monitoring in the community requires parallel analytic systems to interpret the data and automate required medical interventions (SOURCE5).

As for under-the-radar studies or initiatives, there is limited information in the provided sources about specific studies. However, one study mentioned the use of a smart wearable to predict the onset of cardiovascular disease using data collected from a smartwatch for continuous, long-term, and real-time monitoring (SOURCE3). Additionally, future research will focus on long-term implementation of wearables in diverse real-world scenarios to obtain longitudinal data (SOURCE5).