QF-Pro Applications & Clinical Evidence

Each linked term on this page has its own QF-Pro section with the evidence, clinical context and references. Entries are labeled with one of three tiers:

• Clinically validated: a peer-reviewed patient cohort with an outcome association. In these studies, the functional measurement was associated with survival where an expression measurement of the same target was not.
• Validated by HAWK: the assay is on HAWK's List of Validated Biomarkers or described as validated in HAWK's documents, but no outcome cohort has been published.
• Exploratory: neither. These targets have a biological rationale but no HAWK validation data yet.

The common thread: measuring whether proteins are bound or activated can carry information that measuring how much protein is present does not.

Three lines of evidence underpin QF-Pro. Each shows the same pattern: the functional state of a protein carried outcome information that its expression did not.

PD-1/PD-L1 interactionLoading... (clinically validated). In 188 NSCLC patients treated with anti-PD-1/PD-L1 drugs, interaction did not correlate with PD-L1 expression. In the 135 with full clinical data, those above a mean FRET efficiency of 2.127% (the top 40%) had a median overall survival of 31 months versus 10 months, while the clinical PD-L1 cutoff gave no significant difference; the cutoff was chosen from the same cohort.^[5] In 176 patients with malignant melanoma, most of them untreated (148 of 176), PD-1/PD-L1 interaction state measured by iFRET was associated with overall survival (log-rank P = 0.05), while PD-L1 expression was not (P = 0.87).^[3] In clear cell renal cell carcinoma, iFRET detected significant interaction in 11 of 12 patients classed PD-L1-negative by IHC.^[3]

PKB/Akt activationLoading... (clinically validated). Akt activation measured by amplified FRET correlated with shorter disease-free (P = 0.036) and overall survival (P = 0.013) in 164 breast cancer patients, where the intensity ratio did not^[1], and with shorter overall survival in 60 ccRCC patients (hazard ratio 0.228, P = 0.002), where phospho-Akt IHC did not.^[2]

CTLA-4/CD80 interactionLoading... (validated by HAWK). CTLA-4/CD80 interaction was quantified in patient tissue at 1 to 10 nm for the first time in 2022. CD80 expression did not correlate significantly with interaction state (Spearman r_s = 0.134, P = 0.632), consistent with expression and engagement carrying different information. The study had no outcome data.^[4]

QF-Pro has patient data in six settings. Four have outcome associations; two have tissue measurements without outcomes.

• Non-small cell lung cancerLoading... (clinically validated): PD-1/PD-L1, 188 checkpoint inhibitor-treated patients in a multisite blinded analysis^[5], and 40 anti-PD-1-treated patients in the 2020 study, where lower interaction went with worse survival.^[3] CTLA-4/CD80 was also measured on a 150-core lung cancer tissue microarray.^[4]
• MelanomaLoading... (clinically validated): PD-1/PD-L1 in 176 mostly untreated patients, a prognostic association.^[3] A 2025 pilot of neoadjuvant TVEC in stage II melanoma, with six patients treated at UC Davis, found that responding tumors increased in iFRET efficiency while nonresponding tumors decreased in checkpoint engagement or showed no immune stimulation.^[6]
• Breast cancerLoading... (clinically validated): PKB/Akt activation, 164 patients, DFS P = 0.036, OS P = 0.013.^[1]
• Clear cell renal cell carcinomaLoading... (clinically validated for Akt): Akt activation, 60 patients, hazard ratio 0.228, P = 0.002.^[2] PD-1/PD-L1 interaction was measured in ccRCC tissue without outcome data.^[3]
• Colorectal cancerLoading... lung metastases (validated by HAWK, no outcomes): PD-1/PD-L1 and CTLA-4/CD80 were measured before and after radiofrequency ablation. The pre- and post-RFA samples came from different tumors, a limitation the authors state. Before RFA, PD-1/PD-L1 interaction correlated negatively with intratumoral CD3+ and CD8+ density.^[4]

Across these settings, functional measurement added information beyond expression; the outcome studies were retrospective.

These are the ways QF-Pro is being studied for use. Only the first has outcome data behind it.

• Patient selection: In the retrospective NSCLC cohort, about 24% of patients had high PD-1/PD-L1 interaction but low PD-L1 expression; the authors propose that such patients could benefit from checkpoint therapy.^[5] HAWK describes developing QF-Pro assays with drug partners as candidate companion diagnostics. See patient stratificationLoading..., companion diagnosticsLoading... and ICI therapy selectionLoading....
• Treatment monitoring (exploratory): Whether early functional changes track response has been explored in a six-patient TVEC pilot^[6] and in lung metastases before and after ablation.^[4] See abscopal effectLoading... and biomarker validationLoading....
• Platform technology: intercellular interactions by iFRETLoading... for checkpoints, intracellular activation by aFRETLoading... for kinases. See functional biomarkersLoading....
• Technical foundations: why a 1 to 10 nm FRET readout separates binding from proximity. See immune checkpointsLoading..., PPI detectionLoading..., colocalizationLoading... and two-site assayLoading....

These targets do not yet have published outcome data. Some are already validated as assays by HAWK; the rest are exploratory.

Validated by HAWK (on HAWK's List of Validated Biomarkers):

• LAG-3/MHC-IILoading...: LAG-3 is the target of relatlimab, FDA-approved on March 18, 2022 in a fixed-dose combination with nivolumab (Opdualag) for unresectable or metastatic melanoma in patients 12 years and older
• TIM-3Loading.../Gal-9
• TIGIT/CD155Loading...
• HER2/HER3Loading...
• PKB/PDK1, β-catenin/E-cadherin, and STAT3 activation (pY705 and pS727)

Exploratory (no HAWK validation data):

• Further checkpoint targets: CD226Loading..., CD155Loading... as a shared ligand, VISTALoading...
• Oncogenic signaling: BCR-ABLLoading..., BRAFLoading..., PTENLoading... (read out through Akt activation)
• Immune cell subsets: CAR-TLoading..., dendritic cellsLoading..., TregsLoading...

These are partnership and development opportunities, not established applications.

The evidence on this page comes from peer-reviewed publications from 2014 to 2025 and from HAWK's own documents.

Outcome studies

1. Veeriah S, Leboucher P, de Naurois J, et al. High-throughput time-resolved FRET reveals Akt/PKB activation as a poor prognostic marker in breast cancer. Cancer Res. 2014;74(18):4983-4995. Breast cancer, 164 patients; amplified FRET Akt activation with DFS P = 0.036 and OS P = 0.013; intensity ratio not significant.
2. Miles J, Applebee CJ, Leboucher P, et al. Time resolved amplified FRET identifies protein kinase B activation state as a marker for poor prognosis in clear cell renal cell carcinoma. BBA Clin. 2017;8:97-102. ccRCC, 60 patients; overall survival, hazard ratio 0.228, P = 0.002.
3. Sánchez-Magraner L, Miles J, Baker CL, et al. High PD-1/PD-L1 checkpoint interaction infers tumor selection and therapeutic sensitivity to anti-PD-1/PD-L1 treatment. Cancer Res. 2020;80(19):4244-4257. Melanoma (176), metastatic NSCLC (40 with follow-up) and ccRCC.
4. Miles J, Soubeyran I, Marliot F, et al. Determination of interactive states of immune checkpoint regulators in lung metastases after radiofrequency ablation. Cancers. 2022;14(23):5738. First in situ CTLA-4/CD80 quantification; 150-core lung cancer TMA; no outcome data.
5. Sánchez-Magraner L, Gumuzio J, Miles J, et al. Functional engagement of the PD-1/PD-L1 complex but not PD-L1 expression is highly predictive of patient response to immunotherapy in non-small-cell lung cancer. J Clin Oncol. 2023;41(14):2561-2570. 188 checkpoint inhibitor-treated NSCLC patients.
6. Kirane AR, Lee D, Lowe M, et al. Toward functional biomarkers of response to neoadjuvant oncolytic virus in stage II melanoma: immune-Förster resonance energy transfer and the dynamic tumor immune microenvironment. JCO Oncol Adv. 2025;2:e2400049. Six-patient pilot.

Comment and reviews

• Larijani B, Miles J, Ward SG, Parker PJ. Quantification of biomarker functionality predicts patient outcomes. Br J Cancer. 2021;124:1618-1620. Comment on the 2020 iFRET findings.
• Miles J, Ward SG, Larijani B. The fusion of quantitative molecular proteomics and immune-oncology: a step towards precision medicine in cancer therapeutics. FEBS Lett. 2022;596:2721-2735.
• Larijani B, Miles J. Quantification of protein-protein interactions and activation dynamics: a new path to predictive biomarkers. Biophys Chem. 2022;283:106768.

Sources: the publications above; HAWK List of Validated Biomarkers; HAWK Competitor Analysis; FDA, Opdualag approval notice (2022)