Key Anticancer Peptides (ACPs): Advances in Cancer Treatment

Anti-cancer peptides (ACPs) offer a potentially more targeted way to detect and treat cancer compared to conventional therapies like chemotherapy.

ACPs can discriminate between cancerous and healthy cells, resulting in fewer side effects.

Key Facts:

ACPs can actively penetrate and kill tumor cells or enhance the immune system’s response against tumors
They have high specificity, accuracy, tissue penetration with less toxicity than chemo
ACPs can also be used for cancer imaging and diagnostic applications
AI methods are accelerating the design and enhancement of therapeutic ACPs

Source: Molecules (2023)

Anticancer Peptides to Help Eliminate Cancer?

While surgery, chemotherapy, immunotherapy and radiotherapy have prolonged patients’ lives, cancer remains a leading killer globally.

Chemotherapeutics in particular lack tumor specificity, leading to severe side effects.

And both chemo and radiotherapy can actually promote more aggressive tumor growth over time.

There is an urgent need for more targeted anticancer therapies like ACPs that can discriminate between healthy host cells and malignant tumors.

ACPs have the potential to overcome treatment resistance and reduce side effects due to their unique mechanisms of action.

How Anti-Cancer Peptides May Treat Cancer

ACPs are short chains of amino acids, typically less than 50 units long, which gives them tumor-penetrating abilities.

Many ACPs originate from naturally occurring antimicrobial peptides (AMPs), components of innate immunity in organisms.

AMPs rapidly kill microbes by disrupting their cell membranes, a mechanism that also works against cancer cells. Tumors tend to have high negative surface charge, allowing cationic AMPs to selectively target them.
Once attached to cancer cell membranes, ACPs can directly rupture or penetrate the cells. Some ACPs also stimulate anti-tumor immunity by alerting the immune system to dying cancer cells.
Beyond membrane disruption, ACPs can influence cell signaling involved in proliferation, differentiation, and cell death pathways. This multi-targeting ability helps prevent drug resistance.

Promising Anticancer Peptides (ACPs)

While hundreds of ACPs are under study, some stand out for their therapeutic promise or reveal insights into structure-activity relationships.

Aurein 1.2 – 13 amino acid antimicrobial peptide from Australian frogs; adopts alpha helix structure and showed anticancer activity against 60 human cancer cell lines.
BMAP-27 – 27 amino acid antimicrobial peptide from cow; forms amphipathic alpha helix with anticancer activity against leukemia cells.
BMAP-28 – 28 residue bovine antimicrobial peptide; alpha helical structure exhibited antitumor effects.
Brevinin – 25 amino acid peptide from Chinese frogs; predicted to have mixed alpha helix/beta sheet structure and induce cancer cell death.
Cecropin A – Antimicrobial peptide from silk moths, 34-39 residues long with 2 alpha helices; causes pore formation in cancer cell membranes.
Cecropin B – Moth-derived anticancer peptide similar to Cecropin A; inhibits growth of leukemia and other cancer cells.
Citropin 1.1 – 16 residue alpha helical peptide from Australian tree frogs; showed anticancer activity against various human cancer cell lines.
D-K6L9 – 15 residue synthetic anticancer peptide, 1/3 D-amino acids; selectively kills prostate and other cancer cells.
Gaegurins – Family of 6 frog skin peptides, about 24 residues long, helical; anticancer activity demonstrated against colon, breast and drug-resistant cancer lines.
HMGB1 – Human protein with known antimicrobial and anticancer activities; stimulates immune cells against tumors.
HNP1, HNP2, HNP3 – Human alpha-defensins; 29-30 residue peptides kill leukemia, lymphoma and renal cell carcinoma lines.
hBD3 – 45 residue human beta defensin peptide; anticancer mechanism involves membrane binding and permeation.
LfcinB – 25 amino acid bovine lactoferricin peptide released from lactoferrin; anticancer activity against wide range of solid and liquid tumors.
LL-37 – Active form of human cathelicidin antimicrobial peptide; 37 residues with alpha helical structure; kills oral and gastric cancers.
Magainin 2 – 21 residue helical peptide from frog skin; demonstrated cytotoxicity against lung, bladder and other cancers.
Melittin – Main toxic component of bee venom; 26 amino acid alpha helical peptide that destroys cell membranes including cancer cells.
P18 – 18 residue synthetic alpha helical peptide; selective anticancer toxicity against leukemia and other cancers.
PR-39 – Proline/arginine-rich 39 residue pig cathelicidin, unstructured, with anticancer signaling effects in ovarian and liver cells.
Tachyplesin I – 17 residue anti-cancer peptide from horseshoe crabs; beta sheet structure disrupts tumor cell membranes.

The key to creating more selective and multi-targeting ACP therapies is to leverage both natural sources and synthetic analogues.

Advanced screening techniques help prioritize lead candidates for further optimization en route to clinical trials.

ACP Structures & Mechanisms of Action

ACPs mainly form α-helical or β-sheet structures, separating charged and hydrophobic amino acid groups.

Different conformations relate to their cytotoxic mechanisms:

α-helical ACPs like magainins cluster on cell membranes then either lyse cells or self-assemble into pores.
β-sheet ACPs like human defensins HNP 1-3 seem to open ion channels on membranes, dissipating gradients.
Linearly structured ACPs can enter cells and interact with cytoplasmic signaling proteins.

More complex synthetic ACPs combine helices and/or sheets with flexible hinge regions to synergize membrane and intracellular effects.

There are several models explaining how ACPs permeabilize and rupture cell membranes:

The carpet model: ACPs coat surfaces like a carpet until reaching a threshold density, then destabilize membranes through detergent-like micellization.
The barrel-stave model: ACP alpha helices insert perpendicularly into membranes, clustering together to form pores.
The toroidal pore model: ACPs induce cell membranes to bend back on themselves, creating lipid-lined pores.

In addition, ACPs can activate cell death programs or stimulate anti-tumor immune responses once inside cells.

This multi-targeting ability is a key advantage over single-pathway drugs.

Effects of Tumor Microenvironment on ACP Performance

The abnormal tumor microenvironment provides another way to selectively target malignant cells with ACPs.

Rapidly dividing cancer cells outgrow their blood supplies, creating hypoxic areas with highly acidic pH due to shift to glycolytic metabolism. ACPs can exploit this through:

pH-sensitive conformational changes allowing increased penetration or fusion to nanoparticles.
Cell surface proteases unique to tumors that can activate pro-drug ACPs.

Using ACPs for Cancer Diagnostics

Beyond therapy, ACPs have proven useful in cancer imaging and diagnostics:

Radiolabeled ACPs provide rapid, sensitive tumor imaging with low backgrounds and clearances. Regulatory peptide analogs are common targets.
Some ACPs change fluorescence upon contact with cancer markers. Linked to quantum dots or nanomaterials, they become stable, selective sensors.
Arrays with hundreds of peptide probes aid biomarker discovery and personalized medicine approaches.

The ultimate goal is converting prognostic ACP-based tests into companion theranostics that also treat positive cases.

Synthesis and Modification of ACPs

Optimizing ACP sequences and structures is vital to improve selectivity and effectiveness. Common approaches include:

Solid-phase synthesis to quickly generate many ACP analogs with unnatural amino acids or chemical modifications.
Main chain or side chain modifications alter key traits like charge, hydrophobicity, stability and conformation.
Lipid or polymer couplings provide enhanced uptake and half-lives and reduce toxicity to healthy cells.

AI-Assisted Design of Anticancer Peptides

Harnessing big datasets and deep learning, AI systems now accelerate discovery of improved ACPs:

Machine learning algorithms train on experimentally validated ACP sequences to predict new candidates out of vast options.
Deep learning techniques extract subtle patterns within training data, removing need for human-engineered features.
Hybrid AI approaches combine learned feature extraction with traditional statistical classifiers like random forests.
Multitasking models simultaneously predict ACP efficacy against different cancer types.

Future Outlook for ACP-Based Cancer Therapies

While more research is still needed, ACPs have the potential to significantly expand our anticancer arsenal. Key areas for ongoing work include:

Further elucidating ACP structure-activity relationships and cytotoxic mechanisms using advanced spectroscopy and simulations.
Expanding biomedical applications through continued AI exploration of sequence spaces.
Enhancing tumor selectivity and overcoming proteolytic sensitivity via chemical modification and nanocarrier delivery.
Completing human clinical trials to demonstrate efficacy of lead ACP candidates, likely starting with cancers of the blood, skin or urinary tract.

The intrinsic ability of ACPs to discriminate diseased versus healthy host cells positions them at the forefront of next generation targeted cancer therapies.

Both alone and in combination with other emerging treatments, ACPs have the potential to truly move the needle against multiple malignancies that continue to inflict suffering worldwide.

References

Study: Anti-Cancer Peptides: Status and Future Prospects
Authors: Ghaly et al. (2023)