GYNORYLAQ-VLINIVAL is an Early Phase I, non-randomized, single-arm, open-label clinical trial enrolling 40 patients with high-risk or recurrent endometrial carcinoma. All participants receive GYNORYLAQ-TM, a personalized neoantigenic peptide vaccine generated by the GYNORYLAQ-EC™ quantum-classical engine, in combination with systemic and supportive drug regimens that are individually selected and prescribed by the treating medical oncologist, Dr Emmanouelides Christos, according to contemporary standards of care and the clinical status of each patient. Only the GYNORYLAQ-TM vaccine is considered investigational within this protocol; all concomitant drugs (including antineoplastic agents and supportive care medications) are non-investigational, chosen and adjusted at the discretion of Dr Emmanouelides Christos. The primary objectives are to evaluate the safety/tolerability of GYNORYLAQ-TM in this real-world therapeutic context and the feasibility of quantum-guided, GMP-grade personalized vaccine manufacture. Secondary and exploratory objectives characterize vaccine-induced T-cell immunity and explore correlations between quantum/physics-based scores and clinical/immunologic outcomes.

Clinical Background

Endometrial carcinoma is the most common gynecologic malignancy in developed regions. While many early-stage tumours are cured with surgery ± radiotherapy, patients with high-risk, recurrent, or metastatic disease frequently experience relapse after standard therapy and have limited durable options. Particularly poor prognoses are seen in:

Copy-number-high / p53-mutated and serous histologies pMMR tumours with "cold" microenvironments and modest immunotherapy responses MMRd/MSI-H tumours that initially respond to PD-1 blockade but often ultimately progress Across these molecular subtypes, tumours generate patient-specific neoantigens from point mutations, indels, frameshifts in coding microsatellites, fusions, and splice alterations. These mutant peptides can be processed and presented on HLA class I and II molecules, where they may be recognized by T cells as "non-self." This provides a biologically compelling target space for personalized neoantigen vaccination.

However, conventional neoantigen pipelines are largely sequence-based, dependent on binding predictors and heuristic scoring, with limited use of structural information, energetics, or explicit uncertainty quantification. Clinically, many vaccine trials have paired neoantigen constructs with fixed chemotherapy or checkpoint regimens that do not reflect the heterogeneity of real-world oncology practice.

GYNORYLAQ-VLINIVAL is designed to address both issues. It integrates a physics-aware, quantum-classical computational vaccine platform (GYNORYLAQ-EC™) with individualized clinical oncology practice:

All enrolled patients receive a GYNORYLAQ-EC-selected personalized neoantigenic peptide vaccine (GYNORYLAQ-TM).

Systemic and supportive drug therapy is not fixed by protocol. Instead, it is selected, initiated, and adjusted by the treating medical oncologist, Dr Emmanouelides Christos, according to tumour stage, prior treatments, organ function, comorbidities, tolerability, and contemporary guidelines.

The study thus evaluates GYNORYLAQ-TM in a realistic multimodal context, layered on top of individualized best-available care rather than a single mandated backbone. All concomitant antineoplastic and supportive agents are recorded but not dictated by the protocol.

GYNORYLAQ-EC™ Quantum-Classical Vaccinology

GYNORYLAQ-EC™ is the computational core that maps genomic and transcriptomic data into a quantum-entangled design state and, ultimately, into a manufacturable, patient-specific peptide panel. It makes explicit and auditable the chain:

Sequence → Geometry → Structure → Energy → Decision

1. Hilbert Spaces and Global Design State

   The engine is formalized in terms of three Hilbert spaces:

   Sequence space H_"seq" Basis: {∣p_i⟩}, where each basis vector corresponds to a candidate neoantigen peptide (typically 8-11mer class I and longer peptides for class II / cross-presentation).

   HLA space H_"HLA" Basis: {∣〖"HLA" 〗_α⟩}, representing the patient's specific class I and II alleles.

   Immune/tumour space H_"immune" Basis: {∣〖"TCR" 〗_β⟩⊗∣〖"tumour_state" 〗_k⟩}, capturing an abstract TCR repertoire and coarse-grained tumour states (e.g., burden, clonality, immune infiltration).

   The total Hilbert space is:

   H=H_"seq" ⊗H_"HLA" ⊗H_"immune" .

   A formal design-time state ∣Ψ_s⟩∈H evolves through computational blocks (enumeration, scoring, gating, amplification) toward a final design state ∣Ψ_T⟩ whose "support" corresponds to peptides selected for clinical manufacture.

2. Initial Superposition and Grover-Style Entangled Search From tumour and matched normal sequencing, the pipeline enumerates a set of candidate peptides {p_i }_(i=1)^N ┤derived from high-confidence somatic variants, flanked appropriately for presentation. Each candidate is associated with one or more patient HLAs.

   In the idealized quantum picture, the engine constructs an equal superposition over candidates in sequence space:

   ∣Φ_"start" ⟩=1/√N ∑_(i=1)^N▒∣ p_i⟩.

   Each peptide-HLA pair p is also embedded as a normalized quantum state in an n-qubit Hilbert space:

   ∣ψ(p)⟩=U(z_Q (p),θ)" "∣0⟩^(⊗n),

   where: U(⋅) is a parametrized feature map (data-reuploading circuit with fixed entanglers), z_Q (p) is a low-dimensional classical quantum descriptor, θ is a vector of trainable parameters.

   The quantum kernel and Fubini-Study distance between two candidates p and q are:

   K_Q (p,q)=∣⟨ψ(p)∣ψ(q)⟩∣^2, d_"FS" (p,q)=arccos⁡(∣⟨ψ(p)∣ψ(q)⟩∣)∈[0,π/2].

   d_"FS" =0 corresponds to identical rays, d_"FS" =π/2 to orthogonal states. K_Q can be interpreted as the probability that ∣ψ(p)⟩ is projected onto ∣ψ(q)⟩. Peptides with low sequence identity but similar higher-order physicochemical structure may map close together on this manifold, generating large K_Q even when classical similarity is low.

   To implement Grover-style search, the engine defines a marking predicate f(i) such that:

   f(i)=1 if peptide p_i passes three concordant gates: Geometry: d_"FS" to a trusted set of experimentally validated epitopes lies within a predefined window.

   Thermodynamics: binding affinity predicted via ΔG° and K_d^"eff" exceeds prespecified thresholds.

   Immunogenicity: calibrated probability I ̂(p_i) is above a minimum value.

   The phase oracle acting on sequence space is:

   O ̂_"mark" ∣p_i⟩=(-1)^(f(i))∣p_i⟩.

   A diffusion operator reflecting about the mean of the initial superposition, D=2∣Φ_"start" ⟩⟨Φ_"start" ∣-I,

   is combined with the oracle to form the Grover iterate: G=D" " O ̂_"mark" .

   After r iterations,

   ∣Φ_r⟩=G^r∣Φ_"start" ⟩=sin⁡((2r+1)θ)" "∣"good"⟩+cos⁡((2r+1)θ)" "∣"bad"⟩,

   where 〖sin⁡〗^2 θ=M/N and M is the (unknown) number of marked peptides. GYNORYLAQ-EC™ intentionally uses small r (typically 1-3) to produce a shallow, interpretable amplitude amplification of promising peptides, robust to uncertainty in M and to NISQ-era noise.

3. Unified Feature Representation and Composite Kernel

   For each candidate peptide-HLA pair p, GYNORYLAQ-EC™ constructs a unified feature vector:

   Φ(p)=[e_"CNN" (p)," aux"(p)," " z_Q (p)," " ϕ_"struct" (p)," " ϕ_"dock" (p)].

   Components:

   Deep sequence/HLA embedding e_"CNN" (p) Derived from convolutional or transformer models trained on large immunopeptidome datasets, capturing allele-specific binding motifs and sequence context.

   Auxiliary biological priors "aux"(p) Proteasomal cleavage likelihood, TAP transport propensity, transcript expression (TPM/FPKM), allelic copy number, clonality (clonal vs subclonal variants), and when available, ctDNA/MRD readouts. This approximates the effective antigen source strength.

   Quantum descriptor z_Q (p) Low-dimensional classical feature vector parameterizing the quantum circuit. It compresses physicochemical and positional information optimized for quantum expressivity.

   Structural term ϕ_"struct" (p) Summarizes pocket occupancy, peptide-HLA contact patterns, solvent accessibility, and local strain in predicted or modeled peptide-HLA complexes.

   Docking ensemble features ϕ_"dock" (p) Aggregates pose energies, mean and dispersion of docking scores, RMSD across poses, and measures of conformational diversity.

   Similarity between peptide-HLA candidates p and q is encoded in a composite positive semi-definite kernel:

   K_"total" (p,q)=αK_"CNN" (p,q)+βK_"aux" (p,q)+γK_Q (p,q)+δK_"struct" (p,q)+εK_"dock" (p,q),

   where: K_"CNN" ,K_"aux" ,K_"struct" ,K_"dock" are PSD kernels on the respective feature blocks, K_Q is the quantum kernel described above, α,β,γ,δ,ε≥0 adjust the relative weight of each modality. Because each component kernel is PSD, any non-negative linear combination is PSD, ensuring that K_"total" is suitable for kernel logistic regression or related methods.

   A decision function is:

   f(p)=∑_(i=1)^M▒α_i K_"total" (p,p_i)+b,

   where {p_i } are training peptides and {α_iⓜ,b} are learned coefficients. The immunogenicity probability is I ̂(p)=σ(f(p))=1/(1+e^(-f(p)) ),

   which is then calibrated (e.g., Platt scaling, isotonic regression, or temperature scaling) so that predicted probabilities match observed frequencies as closely as possible. This calibrated I ̂(p) is used in the immunogenicity gate and in downstream analysis.

4. Quantum Geometry, Entanglement, and Regularization Beyond similarity, GYNORYLAQ-EC™ monitors the internal structure and entanglement of quantum states ∣ψ(p)⟩. For a bipartition of the n-qubit system into subsystems A and B, the reduced density matrix on A is ρ_A (p)=Tr_B (∣ψ(p)⟩⟨ψ(p)∣),

   and the von Neumann entanglement entropy is S_A (p)=-Tr[ρ_A (p)log⁡ρ_A (p)].

   A regularization term in the training objective encourages entropy values within a target range, avoiding:

   Trivial product states (S_A≈0) with limited expressive power, and Excessively entangled states with high entropy that may be numerically unstable and difficult to approximate on noisy hardware.

   The quantum Fisher information matrix F(θ) characterizes the sensitivity of the encoded states to parameter changes. Its entries are F_ij (θ)=R[⟨∂_i ψ∣∂_j ψ⟩-⟨∂_i ψ∣ψ⟩" "⟨ψ∣∂_j ψ⟩],

   with ∣∂_i ψ⟩=∂∣ψ(θ)⟩/∂θ_i. Poorly conditioned Fisher matrices (with very small eigenvalues) imply unstable parameter estimates and kernel values. Penalizing ill-conditioned F(θ) promotes well-conditioned embeddings and more robust optimization.

5. Thermodynamic Bridge

   Peptide-HLA binding energetics are estimated from structural docking ensembles and then converted into standard thermodynamic quantities. For each peptide-HLA pair, docking yields a set of microstates with free energies ΔG_i^∘ (kcal·mol-¹). The relationship between standard free energy of binding and dissociation constant is:

   ΔG^∘=RTln⁡K_d,

   with: R=1.987×10^(-3) " " 〖"kcal\cdotpmol" 〗^(-1) 〖"\cdotpK" 〗^(-1), T=310" K" (37 °C), so RT≈0.616" " 〖"kcal\cdotpmol" 〗^(-1).

   An effective association constant is computed from the ensemble:

   K_a^"eff" =∑_i▒w_i exp⁡" ⁣" (ⓜ-(ΔG_i^∘)/RT),K_d^"eff" =1/(K_a^"eff" ),ΔG_"eff" ^∘=-RTln⁡K_a^"eff" ,

   where w_i are normalized weights. Uncertainty in ΔG_i^∘ (e.g., dispersion across poses) is propagated to yield uncertainty bands on K_d^"eff" (typically reported in nM). Prespecified thresholds on ΔG_"eff" ^∘ and K_d^"eff" define a unit-consistent binding gate, ensuring that retained peptides are predicted to bind with sufficient affinity under physiologic conditions.

6. Immunogenicity and Benefit-Risk Functional

   The calibrated classifier outputs I(p), a probability of T-cell recognition for each peptide-HLA pair. Conceptually, GYNORYLAQ-EC™ also defines a benefit-risk operator:

   O ̂=O ̂_"benefit" -λO ̂_"risk" ,

   on H_"immune" ⊗H_"tumour" , where: O ̂_"benefit" rewards states with high frequencies of vaccine-matched effector/memory TCR configurations and low tumour burden.

   O ̂_"risk" penalizes states associated with excessive systemic peptide exposure, off-target similarity to critical self-proteins, or overly broad activation.

   For a notional evolution operator U_"tot" (θ),

   ∣Ψ_T (θ)⟩=U_"tot" (θ)∣Ψ_0⟩,J(θ)=⟨Ψ_T (θ)∣O ̂∣Ψ_T (θ)⟩.

   In practice, this expression summarizes a multi-objective optimization: the final GYNORYLAQ-TM panel is chosen to approximate a high-J(θ) subset while obeying manufacturing, safety, and panel-size constraints.

7. Clinical Output: GYNORYLAQ-TM Panel

After passing geometry, thermodynamics, and immunogenicity gates and undergoing shallow Grover-style amplification, candidate peptides are further screened through classical manufacturability and safety filters:

Synthetic feasibility and solubility. Avoidance of highly problematic motifs (e.g., extreme hydrophobic or polybasic regions that compromise formulation).

Proteome-wide scans for near-self matches in critical human proteins, with stringent triage of peptides at risk for dangerous cross-reactivity.

This yields a patient-specific GYNORYLAQ-TM panel, typically comprising ~10-20 peptides:

Multiple 8-11mer class I epitopes spanning key HLA alleles, and Selected longer peptides (e.g., 15-35mers) that support class II presentation and robust CD4⁺ T-cell help.

All selected peptides are synthesized under GMP and formulated for subcutaneous or intradermal administration.

Investigational Product and Concomitant Drug Use Investigational Product Name: GYNORYLAQ-TM Personalized Neoantigenic Peptide Vaccine Type: Biological (synthetic peptide mixture) Composition: Patient-specific collection of GYNORYLAQ-EC-selected neoantigenic peptides (short class I and longer helper peptides).

Route of Administration: Subcutaneous or intradermal injection. Planned Early Phase I Vaccination Schedule (Non-Randomized) Priming phase: Approximately Weeks 0, 2, 4, and 8. Booster phase (optional): Additional doses around Months 6 and 12 in patients without prohibitive toxicity who appear to derive clinical benefit, at the discretion of Dr Emmanouelides Christos and according to protocol-defined criteria.

Exact timing and number of doses may be refined based on emerging safety and immunogenicity data in this early-phase, 40-patient cohort.

Concomitant Drugs and Clinical Management

A key design principle of GYNORYLAQ-VLINIVAL is that systemic antineoplastic and supportive therapy is individualized rather than protocol-mandated:

All decisions about systemic drug treatment are made by the treating medical oncologist, Dr Emmanouelides Christos.

Examples include, but are not limited to:

Cytotoxic chemotherapy (e.g., platinum-based regimens, liposomal anthracyclines).

Hormonal therapy (e.g., progestins, aromatase inhibitors) where appropriate. Targeted agents (e.g., mTOR inhibitors, TKIs) as indicated by tumour biology and guidelines.

Other immunomodulatory agents when clinically justified and permitted by the protocol.

Supportive care medicines (antiemetics, analgesics, anticoagulants, growth factors, management of comorbidities, etc.) are similarly individualized.

These agents are considered non-investigational background therapy. The protocol:

Does not prescribe or prioritize specific drug regimens. Requires detailed documentation of concomitant therapies (drug names, doses, schedules, modifications, and reasons for change).

Imposes only standard safety constraints (e.g., limits on high-dose systemic steroids during key immune monitoring windows, minimal washout periods for certain cytotoxics or biologics, exclusion of strongly immunosuppressive regimens that could invalidate immunogenicity assessment).

This design:

Preserves clinical autonomy, allowing Dr Emmanouelides Christos to treat each patient according to best current practice.

Ensures that GYNORYLAQ-TM is evaluated in a real-world multimodal setting, reflective of clinical oncology practice rather than a narrow regimen.

Enables exploratory analyses of how different background treatment classes (e.g., intensive chemotherapy vs endocrine maintenance vs minimal systemic treatment) may influence vaccine-induced immune responses and clinical outcomes.

In summary, GYNORYLAQ-VLINIVAL treats GYNORYLAQ-TM as the single investigational product, layered onto individualized background therapies selected and prescribed by Dr Emmanouelides Christos. The computational pipeline GYNORYLAQ-EC™ provides a fully auditable, quantum-informed, physics-aware mechanism for peptide selection, while the trial structure evaluates feasibility, safety, and immunologic activity under conditions that closely resemble routine care for high-risk endometrial carcinoma.

Inclusion Criteria: Participants must meet all of the following criteria to be eligible:

Informed Consent and Legal Capacity 1.1. Ability to understand the nature of the study and provide written informed consent personally or via a legally authorized representative, in accordance with local regulations.

1.2. Willingness and ability (participant and/or guardian) to comply with scheduled visits, vaccination procedures, blood draws, imaging, and other study-related assessments.

Diagnosis and Histology 2.1. Histologically confirmed endometrial carcinoma (endometrioid, serous, clear cell, mixed histology, carcinosarcoma, or other specified high-risk subtypes), documented by pathology report.

2.2. High-risk, recurrent, or metastatic disease, defined by at least one of: FIGO Stage III or IV at initial diagnosis, and/or Recurrent or progressive disease after prior surgery ± radiotherapy ± systemic therapy, not amenable to curative-intent surgery or radiotherapy.

Disease Status at Enrollment 3.1. Radiologically measurable disease per RECIST v1.1, or evaluable disease if allowed by protocol (e.g., measurable by other validated imaging or biomarker criteria).

3.2. Disease status documented by CT/MRI (or PET/CT, if local standard) within 28 days before the first GYNORYLAQ-TM vaccination.

Prior Anti-cancer Therapy 4.1. Participants may have received prior surgery, radiotherapy, chemotherapy, endocrine therapy, and/or targeted agents, provided all of the following apply:

• 3 weeks since last dose of cytotoxic chemotherapy (≥6 weeks for mitomycin C or nitrosoureas).
• 2 weeks since last dose of endocrine therapy (if applicable).
• 4 weeks (or 5 half-lives, whichever is longer) since last dose of any investigational systemic agent or biologic therapy.
• 2 weeks since completion of palliative radiotherapy to non-CNS sites, with radiotherapy-related toxicities recovered to Grade ≤1 (CTCAE v5.0).

4.2. Recovery from acute toxicity of prior therapies to Grade ≤1 or baseline (CTCAE v5.0), except for: Alopecia, Stable peripheral neuropathy (≤Grade 2), Other protocol-specified exceptions. 4.3. Prior immune checkpoint inhibitor therapy (e.g., anti-PD-1/PD-L1) is allowed, provided there is no history of Grade ≥3 immune-related adverse event that mandated permanent discontinuation.

Suitability for Systemic Therapy (Clinical Practice Integration) 5.1. In the opinion of the treating medical oncologist Dr Emmanouelides Christos, the participant is suitable for ongoing systemic anti-cancer and supportive drug treatment (e.g., chemotherapy, endocrine therapy, targeted therapy) consistent with prevailing guidelines and local standards of care.

5.2. There is no absolute contraindication to all forms of systemic therapy that might reasonably be selected by Dr Emmanouelides Christos.

5.3. The participant agrees that systemic and supportive drugs will be chosen, initiated, and adjusted by Dr Emmanouelides Christos and recorded as background therapy.

Tumour Tissue and Blood Availability 6.1. Availability of sufficient tumour material for sequencing and neoantigen discovery: Fresh tumour tissue from recent biopsy or surgery (preferred) obtained within approximately the last 6 months, or Adequate archival FFPE tumour tissue (block or unstained slides) deemed sufficient by the central laboratory for DNA/RNA extraction.

6.2. Availability of matched normal sample (e.g., peripheral blood) for germline reference.

6.3. Willingness, when clinically safe and feasible, to undergo additional tumour biopsy/biopsies for translational and correlative studies per protocol.

Performance Status and Clinical Stability 7.1. Eastern Cooperative Oncology Group (ECOG) performance status 0 or 1. 7.2. Anticipated life expectancy of ≥ 3 months, as judged by the investigator. Adequate Organ and Marrow Function (All labs within 14 days prior to first vaccine dose; repeat as clinically indicated.) 8.1. Hematologic function Absolute neutrophil count (ANC) ≥ 1.5 × 10⁹/L (without growth factor support within 7 days).

Platelets ≥ 100 × 10⁹/L (without transfusion within 7 days). Hemoglobin ≥ 9.0 g/dL (transfusion allowed if stable for ≥1 week). 8.2. Hepatic function Total bilirubin ≤ 1.5 × upper limit of normal (ULN); In participants with documented Gilbert's syndrome, total bilirubin ≤3 × ULN may be allowed if direct bilirubin ≤1.5 × ULN.

AST (SGOT) and ALT (SGPT) ≤ 2.5 × ULN (≤5 × ULN in presence of liver metastases).

Alkaline phosphatase ≤ 2.5 × ULN (≤5 × ULN in presence of bone or liver metastases).

8.3. Renal function Serum creatinine ≤ 1.5 × ULN or Creatinine clearance ≥ 50 mL/min (Cockcroft-Gault or institutional standard). 8.4. Coagulation (if clinically indicated) INR and aPTT within institutional normal limits or medically acceptable for participants on stable anticoagulation.

Infection and Virology 9.1. No uncontrolled active infection requiring IV antibiotics or hospitalization.

9.2. Hepatitis B (HBV): Participants with resolved infection (HBsAg-, anti-HBc+) and undetectable HBV DNA may be included with monitoring.

Participants with chronic HBV (HBsAg+) may be eligible if HBV DNA is adequately suppressed under antiviral therapy and hepatic function meets criteria.

9.3. Hepatitis C (HCV): Participants with HCV antibody positivity may be included if HCV RNA is negative or controlled on therapy and hepatic function is acceptable.

9.4. HIV: Participants with HIV infection may be eligible if on a stable antiretroviral regimen with suppressed viral load and CD4 count above a protocol-defined threshold (e.g., ≥200 cells/μL), without uncontrolled opportunistic infections.

Reproductive Potential and Contraception 10.1. Participants who are capable of causing pregnancy or becoming pregnant must have no evidence of ongoing pregnancy at baseline (e.g., negative pregnancy test where applicable and per local regulations) and must agree to use highly effective contraception or remain abstinent from sexual activity that could result in pregnancy for at least 6 months after the last GYNORYLAQ-TM vaccination.

10.2. Contraception methods may include, but are not limited to: hormonal contraceptives, intrauterine devices, or a combination of barrier methods, as per local guidelines and clinical judgment.

10.3. Participants who are permanently infertile (e.g., surgical sterilization) or post-reproductive (per local definitions) are not required to use contraception.

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Exclusion Criteria: Participants meeting any of the following will be excluded:

Tumour and Disease Characteristics 1.1. Cancers not consistent with endometrial carcinoma as primary site (e.g., primary cervical or ovarian carcinoma) unless clearly documented as metastatic/endometrial in origin.

1.2. Disease requiring urgent, life-saving intervention that would preclude safe vaccine administration (e.g., impending organ failure requiring immediate surgery or high-dose radiotherapy).

1.3. Disease burden or rate of progression such that, in the opinion of the investigator and/or Dr Emmanouelides Christos, any delay associated with vaccine manufacturing and initiation of protocol therapy would be unsafe.

Prior Therapies and Confounding Investigational Products 2.1. Prior receipt of neoantigen-specific or tumour vaccine products that target highly overlapping epitope sets in a way that would confound interpretation of GYNORYLAQ-TM-induced responses, unless approved case-by-case.

2.2. Participation in another interventional clinical trial with therapeutic intent or receipt of an investigational systemic agent within 4 weeks (or 5 half-lives, whichever is longer) before first GYNORYLAQ-TM dose, unless discussed with and approved by the sponsor/investigator.

2.3. Prior allogeneic hematopoietic stem cell or solid organ transplantation. Autoimmune and Immune-mediated Conditions 3.1. Active, known, or suspected autoimmune disease requiring systemic immunosuppressive treatment (e.g., ≥10 mg/day prednisone equivalent) within the past 12 months, including but not limited to: Systemic lupus erythematosus Inflammatory bowel disease (Crohn's disease, ulcerative colitis) Multiple sclerosis Severe rheumatoid arthritis, systemic sclerosis, vasculitis Autoimmune hepatitis 3.2. Acceptable exceptions may include: Controlled autoimmune thyroiditis on stable hormone replacement Vitiligo, type 1 diabetes mellitus, or psoriasis not requiring systemic immunosuppression Other minor or stable autoimmune conditions deemed acceptable by the investigator.

3.3. Primary or acquired immunodeficiency states (other than controlled HIV as per inclusion criteria) that, in the investigator's judgment, could significantly compromise vaccine-induced immune responses or increase risk.

Concomitant Immunosuppressive Therapy 4.1. Chronic systemic immunosuppressive therapy including: Steroid therapy equivalent to >10 mg/day prednisone for more than 14 consecutive days within 30 days prior to first vaccine dose, or Other immunosuppressive agents (e.g., calcineurin inhibitors, mTOR inhibitors, anti-TNF agents) without a washout period acceptable to the investigator.

4.2. Short-term steroid use (e.g., antiemetic prophylaxis, contrast premedication, acute reaction management) is permitted as long as it is not chronic.

Central Nervous System Disease 5.1. Untreated or unstable CNS metastases or carcinomatous meningitis. 5.2. Participants with previously treated CNS metastases may be eligible if all of the following are true: Radiologically stable or responding for ≥4 weeks after completion of CNS-directed therapy, and Neurologically stable, and Off systemic corticosteroids (or on physiologic replacement doses only) for ≥2 weeks prior to first vaccine dose.

Cardiovascular, Pulmonary, and Other Serious Comorbidities 6.1. Clinically significant, uncontrolled cardiovascular disease, including: Myocardial infarction within 6 months, Unstable angina, Significant uncontrolled arrhythmias (excluding controlled atrial fibrillation), Symptomatic congestive heart failure (NYHA Class III-IV), Uncontrolled hypertension (e.g., systolic ≥180 mmHg or diastolic ≥100 mmHg despite treatment).

6.2. History of venous thromboembolism (DVT/PE) that is not adequately anticoagulated, or acute events within 4 weeks prior to screening that pose high risk in the investigator's judgment.

6.3. Severe, uncontrolled pulmonary disease, such as advanced COPD, interstitial lung disease with active symptoms, or chronic oxygen dependence that would substantially increase risk.

Active Infections 7.1. Active, uncontrolled bacterial, viral, or fungal infection requiring IV therapy or hospitalization.

7.2. Confirmed active tuberculosis infection. 7.3. Uncontrolled chronic HBV, HCV, or HIV infection not meeting the inclusion conditions.

Other Malignancies 8.1. Another active malignancy within the past 3 years, excluding: Curatively treated non-melanoma skin cancers, In situ carcinoma (e.g., cervical, breast, bladder) treated with curative intent, Other malignancies considered by the investigator to have negligible risk of recurrence and unlikely to interfere with study participation or interpretation.

Hypersensitivity 9.1. Known severe hypersensitivity or anaphylaxis to any component of the GYNORYLAQ-TM peptide vaccine or its excipients.

9.2. History of severe hypersensitivity reactions to multiple injectable biologics that, in the investigator's judgment, substantially increase risk.

Vaccination Confounders 10.1. Receipt of live attenuated vaccines within 4 weeks before the first GYNORYLAQ-TM dose or planned receipt of live vaccines during protocol-defined at-risk periods (e.g., within 4 weeks after last vaccine dose).

10.2. Receipt of non-live vaccines within 7 days prior to GYNORYLAQ-TM vaccination that, in the investigator's judgment, could substantially confound immunologic readouts (standard seasonal inactivated influenza and COVID-19 vaccines may be allowed per protocol).

Pregnancy and Breastfeeding 11.1. Known ongoing pregnancy at screening or baseline. 11.2. Breastfeeding participants, if the investigator believes there may be potential risk to the infant and interruption of breastfeeding is not acceptable to the participant.

Compliance and Investigator Judgment 12.1. Any psychiatric, cognitive, social, or substance abuse condition that, in the investigator's opinion, would interfere with study compliance or the ability to follow protocol requirements.

12.2. Any other serious medical or non-medical condition which, in the opinion of the investigator and/or Dr Emmanouelides Christos, would place the participant at undue risk, compromise data integrity, or make them unsuitable for the trial.

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Individual participant data (IPD) will not be shared because the GYNORYLAQ-TM platform and its underlying quantum-classical neoantigen selection methods are the subject of an ongoing patent application. Data sharing will be reconsidered after the patent process is complete and the associated intellectual property protections are clarified.